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Witold Pedrycz - Publications

Affiliations: 
Electrical and Computer Engineering University of Alberta, Edmonton, Alberta, Canada 
Area:
Computer Engineering, Artificial Intelligence
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Year Citation  Score
2024 Liu S, Oh SK, Pedrycz W, Yang B, Wang L, Seo K. Fuzzy Adaptive Knowledge-Based Inference Neural Networks: Design and Analysis. Ieee Transactions On Cybernetics. PMID 38416627 DOI: 10.1109/TCYB.2024.3353753  0.365
2023 Zhang T, Zhang Y, Ma F, Peng C, Yue D, Pedrycz W. Local Boundary Fuzzified Rough K -Means-Based Information Granulation Algorithm Under the Principle of Justifiable Granularity. Ieee Transactions On Cybernetics. PMID 37030830 DOI: 10.1109/TCYB.2023.3257274  0.319
2022 Zhang C, Oh SK, Fu Z, Pedrycz W. Incremental Fuzzy Clustering-Based Neural Networks Driven With the Aid of Dynamic Input Space Partition and Quasi-Fuzzy Local Models. Ieee Transactions On Cybernetics. PMID 37015632 DOI: 10.1109/TCYB.2022.3228303  0.374
2022 Liu P, Li Y, Zhang X, Pedrycz W. A Multiattribute Group Decision-Making Method With Probabilistic Linguistic Information Based on an Adaptive Consensus Reaching Model and Evidential Reasoning. Ieee Transactions On Cybernetics. PMID 35486566 DOI: 10.1109/TCYB.2022.3165030  0.353
2022 Pedrycz W. Computing and Clustering in the Environment of Order-2 Information Granules. Ieee Transactions On Cybernetics. PMID 35427227 DOI: 10.1109/TCYB.2022.3163350  0.354
2021 Zhu X, Wang D, Pedrycz W, Li Z. A Design of Granular Classifier Based on Granular Data Descriptors. Ieee Transactions On Cybernetics. PMID 34936563 DOI: 10.1109/TCYB.2021.3132636  0.354
2021 Lu W, Ma C, Pedrycz W, Yang J. Design of Granular Model: A Method Driven by Hyper-Box Iteration Granulation. Ieee Transactions On Cybernetics. PMID 34767519 DOI: 10.1109/TCYB.2021.3124235  0.341
2021 Hu X, Shen Y, Pedrycz W, Li Y, Wu G. Granular Fuzzy Rule-Based Modeling With Incomplete Data Representation. Ieee Transactions On Cybernetics. PMID 33909582 DOI: 10.1109/TCYB.2021.3071145  0.387
2021 Hu X, Shen Y, Pedrycz W, Wang X, Gacek A, Liu B. Identification of Fuzzy Rule-Based Models With Collaborative Fuzzy Clustering. Ieee Transactions On Cybernetics. PMID 33878000 DOI: 10.1109/TCYB.2021.3069783  0.377
2021 Liang Y, Ju Y, Qin J, Pedrycz W. Multi-granular linguistic distribution evidential reasoning method for renewable energy project risk assessment Information Fusion. 65: 147-164. DOI: 10.1016/J.Inffus.2020.08.010  0.32
2020 Zhu X, Pedrycz W, Li Z. A Granular Approach to Interval Output Estimation for Rule-Based Fuzzy Models. Ieee Transactions On Cybernetics. PMID 33151886 DOI: 10.1109/TCYB.2020.3025668  0.301
2020 Zhu X, Pedrycz W, Li Z. A Two-Stage Approach for Constructing Type-2 Information Granules. Ieee Transactions On Cybernetics. PMID 32721903 DOI: 10.1109/Tcyb.2020.2965967  0.428
2020 Tang M, Liao H, Herrera-Viedma E, Chen CLP, Pedrycz W. A Dynamic Adaptive Subgroup-to-Subgroup Compatibility-Based Conflict Detection and Resolution Model for Multicriteria Large-Scale Group Decision Making. Ieee Transactions On Cybernetics. PMID 32149679 DOI: 10.1109/Tcyb.2020.2974924  0.385
2020 Tan A, Shi S, Wu WZ, Li J, Pedrycz W. Granularity and Entropy of Intuitionistic Fuzzy Information and Their Applications. Ieee Transactions On Cybernetics. PMID 32142467 DOI: 10.1109/Tcyb.2020.2973379  0.408
2020 Guo H, Wang L, Liu X, Pedrycz W. Information Granulation-Based Fuzzy Clustering of Time Series. Ieee Transactions On Cybernetics. PMID 32112690 DOI: 10.1109/Tcyb.2020.2970455  0.418
2020 Han Z, Pedrycz W, Zhao J, Wang W. Hierarchical Granular Computing-Based Model and Its Reinforcement Structural Learning for Construction of Long-Term Prediction Intervals. Ieee Transactions On Cybernetics. PMID 32011274 DOI: 10.1109/Tcyb.2020.2964011  0.352
2020 Wu Y, Dong Y, Qin J, Pedrycz W. Linguistic Distribution and Priority-Based Approximation to Linguistic Preference Relations With Flexible Linguistic Expressions in Decision Making. Ieee Transactions On Cybernetics. PMID 31995508 DOI: 10.1109/Tcyb.2019.2953307  0.344
2020 Meng FY, Tang J, Pedrycz W, An QX. Optimal Interaction Priority Calculation From Hesitant Fuzzy Preference Relations Based on the Monte Carlo Simulation Method for the Acceptable Consistency and Consensus. Ieee Transactions On Cybernetics. PMID 31945009 DOI: 10.1109/Tcyb.2019.2962095  0.447
2020 Tian G, Hao N, Zhou M, Pedrycz W, Zhang C, Ma F, Li Z. Fuzzy Grey Choquet Integral for Evaluation of Multicriteria Decision Making Problems With Interactive and Qualitative Indices Ieee Transactions On Systems, Man, and Cybernetics. 1-14. DOI: 10.1109/Tsmc.2019.2906635  0.468
2020 Du S, Wu M, Chen L, Zhou K, Hu J, Cao W, Pedrycz W. A Fuzzy Control Strategy of Burn-Through Point Based on the Feature Extraction of Time-Series Trend for Iron Ore Sintering Process Ieee Transactions On Industrial Informatics. 16: 2357-2368. DOI: 10.1109/Tii.2019.2935030  0.384
2020 Zhang B, Pedrycz W, Wang X, Gacek A. Design of Interval Type-2 Information Granules Based on the Principle of Justifiable Granularity Ieee Transactions On Fuzzy Systems. 1-1. DOI: 10.1109/Tfuzz.2020.3023758  0.344
2020 Zhang C, Oh S, Fu Z, Pedrycz W. Design of Reinforced Hybrid Fuzzy Rule-based Neural Networks Driven to Inhomogeneous Neurons and Tournament Selection Ieee Transactions On Fuzzy Systems. 1-1. DOI: 10.1109/Tfuzz.2020.3018190  0.377
2020 Zhang B, Li C, Dong Y, Pedrycz W. A Comparative Study Between Analytic Hierarchy Process and Its Fuzzy Variants: A Perspective based on Two Linguistic Models Ieee Transactions On Fuzzy Systems. 1-1. DOI: 10.1109/Tfuzz.2020.3018110  0.396
2020 Bui Q, Vo B, Snasel V, Pedrycz W, Hong TP, Nguyen N, Chen M. SFCM: A Fuzzy Clustering Algorithm of Extracting the Shape Information of Data Ieee Transactions On Fuzzy Systems. 1-1. DOI: 10.1109/Tfuzz.2020.3014662  0.423
2020 Mamaghani AS, Pedrycz W. Genetic-Programming based Architecture of Fuzzy Modeling: Towards Coping with High-dimensional Data Ieee Transactions On Fuzzy Systems. 1-1. DOI: 10.1109/Tfuzz.2020.3006993  0.378
2020 Zhang B, Dong Y, Feng X, Pedrycz W. Maximum Fuzzy Consensus Feedback Mechanism with Minimum Cost and Private Interest in Group Decision Making Ieee Transactions On Fuzzy Systems. 1-1. DOI: 10.1109/Tfuzz.2020.3006559  0.361
2020 Gao D, Wang G, Pedrycz W. Solving Fuzzy Job-shop Scheduling Problem Using DE Algorithm Improved by a Selection Mechanism Ieee Transactions On Fuzzy Systems. 1-1. DOI: 10.1109/Tfuzz.2020.3003506  0.371
2020 Liu P, wang P, Pedrycz W. Consistency- and consensus-based group decision-making method with incomplete probabilistic linguistic preference relations Ieee Transactions On Fuzzy Systems. 1-1. DOI: 10.1109/Tfuzz.2020.3003501  0.307
2020 Yang C, Oh S, Pedrycz W, Fu Z, Yang B. Design of Reinforced Fuzzy Radial Basis Function Neural Networks Classifier Driven with the Aid of Iterative Learning Techniques and Support Vector-based Clustering Ieee Transactions On Fuzzy Systems. 1-1. DOI: 10.1109/Tfuzz.2020.3001740  0.409
2020 Lu W, Pedrycz W, Yang J, Liu X. Granular Description with Multi-Granularity for Multidimensional Data: A Cone-Shaped Fuzzy Set-Based Method Ieee Transactions On Fuzzy Systems. 1-1. DOI: 10.1109/Tfuzz.2020.2985335  0.487
2020 Cui Y, E H, Pedrycz W, Li Z. Designing Distributed Fuzzy Rule-Based Models Ieee Transactions On Fuzzy Systems. 1-1. DOI: 10.1109/Tfuzz.2020.2984971  0.415
2020 Liu F, Huang M, Pedrycz W, Zhao H. Group decision making based on flexibility degree of fuzzy numbers under a confidence level Ieee Transactions On Fuzzy Systems. 1-1. DOI: 10.1109/Tfuzz.2020.2983663  0.397
2020 Ding W, Pedrycz W, Lin C. Guest Editorial for the Special Issue on Fuzzy Rough Sets for Big Data Ieee Transactions On Fuzzy Systems. 28: 803-805. DOI: 10.1109/Tfuzz.2020.2979204  0.438
2020 Ding W, Pedrycz W, Triguero I, Cao Z, Lin C. Multigranulation Super-Trust Model for Attribute Reduction Ieee Transactions On Fuzzy Systems. 1-14. DOI: 10.1109/Tfuzz.2020.2975152  0.495
2020 Zhang B, Pedrycz W, Fayek AR, Gacek A, Dong Y. Granular Aggregation of Fuzzy Rule-Based Models in Distributed Data Environment Ieee Transactions On Fuzzy Systems. 1-1. DOI: 10.1109/Tfuzz.2020.2973956  0.416
2020 Gupta P, Mehlawat MK, Khaitan A, Pedrycz W. Sentiment Analysis for Driver Selection in Fuzzy Capacitated Vehicle Routing Problem with Simultaneous Pick-up and Drop in Shared Transportation Ieee Transactions On Fuzzy Systems. 1-1. DOI: 10.1109/Tfuzz.2020.2970834  0.353
2020 Yang X, Yu F, Pedrycz W. Typical Characteristics-based Type-2 Fuzzy C-Means Algorithm Ieee Transactions On Fuzzy Systems. 1-1. DOI: 10.1109/Tfuzz.2020.2969907  0.402
2020 Liu Y, Zhao J, Wang D, Pedrycz W. Prediction Intervals for Granular Data Streams Based on Evolving Type-2 Fuzzy Granular Neural Network Dynamic Ensemble Ieee Transactions On Fuzzy Systems. 1-1. DOI: 10.1109/Tfuzz.2020.2966172  0.404
2020 Chen L, Su W, Wu M, Pedrycz W, Hirota K. A Fuzzy Deep Neural Network With Sparse Autoencoder for Emotional Intention Understanding in Human–Robot Interaction Ieee Transactions On Fuzzy Systems. 28: 1252-1264. DOI: 10.1109/Tfuzz.2020.2966167  0.346
2020 Mehlawat MK, Gupta P, Khaitan A, Pedrycz W. A Hybrid Intelligent Approach to Integrated Fuzzy Multiple Depot Capacitated Green Vehicle Routing Problem With Split Delivery and Vehicle Selection Ieee Transactions On Fuzzy Systems. 28: 1155-1166. DOI: 10.1109/Tfuzz.2019.2946110  0.415
2020 Pratama M, Pedrycz W, Webb GI. An Incremental Construction of Deep Neuro Fuzzy System for Continual Learning of Nonstationary Data Streams Ieee Transactions On Fuzzy Systems. 28: 1315-1328. DOI: 10.1109/Tfuzz.2019.2939993  0.413
2020 Zhang Z, Wu C, Pedrycz W. A Novel Group Decision-Making Method for Interval-Valued Intuitionistic Multiplicative Preference Relations Ieee Transactions On Fuzzy Systems. 28: 1799-1814. DOI: 10.1109/Tfuzz.2019.2922917  0.379
2020 Kim E, Oh S, Pedrycz W, Fu Z. Reinforced Fuzzy Clustering-Based Ensemble Neural Networks Ieee Transactions On Fuzzy Systems. 28: 569-582. DOI: 10.1109/Tfuzz.2019.2911492  0.414
2020 Ping X, Pedrycz W. Output Feedback Model Predictive Control of Interval Type-2 T–S Fuzzy System With Bounded Disturbance Ieee Transactions On Fuzzy Systems. 28: 148-162. DOI: 10.1109/Tfuzz.2019.2900844  0.325
2020 Rong M, Gong D, Pedrycz W, Wang L. A Multimodel Prediction Method for Dynamic Multiobjective Evolutionary Optimization Ieee Transactions On Evolutionary Computation. 24: 290-304. DOI: 10.1109/Tevc.2019.2925358  0.301
2020 Wu M, Su W, Chen L, Pedrycz W, Hirota K. Two-stage Fuzzy Fusion based-Convolution Neural Network for Dynamic Emotion Recognition Ieee Transactions On Affective Computing. 1-1. DOI: 10.1109/Taffc.2020.2966440  0.349
2020 Wang H, Li K, Pedrycz W. An Elite Hybrid Metaheuristic Optimization Algorithm for Maximizing Wireless Sensor Networks Lifetime With a Sink Node Ieee Sensors Journal. 20: 5634-5649. DOI: 10.1109/Jsen.2020.2971035  0.303
2020 Wang L, Han Z, Pedrycz W, Zhao J, Wang W. A Granular Computing-Based Hybrid Hierarchical Method for Construction of Long-Term Prediction Intervals for Gaseous System of Steel Industry Ieee Access. 8: 63538-63550. DOI: 10.1109/Access.2020.2983446  0.348
2020 Singla M, Ghosh D, Shukla KK, Pedrycz W. Robust twin support vector regression based on rescaled Hinge loss Pattern Recognition. 105: 107395. DOI: 10.1016/J.Patcog.2020.107395  0.37
2020 Zhang C, Oh S, Co ZF, Pedrycz W. Self-organized Hybrid Fuzzy Neural Networks Driven with the Aid of Probability-based Node Selection and Enhanced Input Strategy Neurocomputing. DOI: 10.1016/J.Neucom.2020.08.072  0.422
2020 Colace F, Loia V, Pedrycz W, Tomasiello S. On a granular functional link network for classification Neurocomputing. 398: 108-116. DOI: 10.1016/J.Neucom.2020.02.090  0.362
2020 Karczmarek P, Kiersztyn A, Pedrycz W, Al E. K-Means-based isolation forest Knowledge Based Systems. 195: 105659. DOI: 10.1016/J.Knosys.2020.105659  0.334
2020 Liu F, Zhang J, Zhang W, Pedrycz W. Decision making with a sequential modeling of pairwise comparison process Knowledge Based Systems. 195: 105642. DOI: 10.1016/J.Knosys.2020.105642  0.358
2020 Fu C, Lu W, Pedrycz W, Yang J. Rule-based granular classification: A hypersphere information granule-based method Knowledge-Based Systems. 194: 105500. DOI: 10.1016/J.Knosys.2020.105500  0.378
2020 Li L, Pedrycz W, Qu T, Li Z. Fuzzy associative memories with autoencoding mechanisms Knowledge Based Systems. 191: 105090. DOI: 10.1016/J.Knosys.2019.105090  0.36
2020 Tang X, Peng Z, Zhang Q, Pedrycz W, Yang S. Consistency and consensus-driven models to personalize individual semantics of linguistic terms for supporting group decision making with distribution linguistic preference relations Knowledge Based Systems. 189: 105078. DOI: 10.1016/J.Knosys.2019.105078  0.391
2020 Zhang Y, Miao D, Pedrycz W, Zhao T, Xu J, Yu Y. Granular structure-based incremental updating for multi-label classification Knowledge Based Systems. 189: 105066. DOI: 10.1016/J.Knosys.2019.105066  0.316
2020 Aliev R, Pedrycz W, Guirimov B, Huseynov O. Clustering method for production of Z-number based if-then rules Information Sciences. 520: 155-176. DOI: 10.1016/J.Ins.2020.02.002  0.485
2020 Meng T, Jing X, Yan Z, Pedrycz W. A survey on machine learning for data fusion Information Fusion. 57: 115-129. DOI: 10.1016/J.Inffus.2019.12.001  0.303
2020 Ghosh D, Debnath AK, Pedrycz W. A variable and a fixed ordering of intervals and their application in optimization with interval-valued functions International Journal of Approximate Reasoning. 121: 187-205. DOI: 10.1016/J.Ijar.2020.03.004  0.334
2020 Xu S, Ju H, Shang L, Pedrycz W, Yang X, Li C. Label distribution learning: A local collaborative mechanism International Journal of Approximate Reasoning. 121: 59-84. DOI: 10.1016/J.Ijar.2020.02.003  0.331
2020 Yun U, Nam H, Kim J, Kim H, Baek Y, Lee J, Yoon E, Truong TC, Vo B, Pedrycz W. Efficient transaction deleting approach of pre-large based high utility pattern mining in dynamic databases Future Generation Computer Systems. 103: 58-78. DOI: 10.1016/J.Future.2019.09.024  0.351
2020 Zhou J, Pedrycz W, Gao C, Lai Z, Yue X. Principles for constructing three-way approximations of fuzzy sets: A comparative evaluation based on unsupervised learning Fuzzy Sets and Systems. DOI: 10.1016/J.Fss.2020.06.019  0.495
2020 Yang C, Oh S, Yang B, Pedrycz W, Fu Z. Fuzzy quasi-linear SVM classifier: Design and analysis Fuzzy Sets and Systems. DOI: 10.1016/J.Fss.2020.05.010  0.446
2020 Xu K, Pedrycz W, Li Z, Nie W. Optimizing the prototypes with a novel data weighting algorithm for enhancing the classification performance of fuzzy clustering Fuzzy Sets and Systems. DOI: 10.1016/J.Fss.2020.05.009  0.389
2020 Kerr-Wilson J, Pedrycz W. Generating a hierarchical fuzzy rule-based model Fuzzy Sets and Systems. 381: 124-139. DOI: 10.1016/J.Fss.2019.07.013  0.483
2020 Mencar C, Pedrycz W. Granular counting of uncertain data Fuzzy Sets and Systems. 387: 108-126. DOI: 10.1016/J.Fss.2019.04.018  0.362
2020 Nguyen D, Luo W, Vo B, Pedrycz W. Succinct Contrast Sets via False Positive Controlling with an Application in Clinical Process Redesign Expert Systems With Applications. 161: 113670. DOI: 10.1016/J.Eswa.2020.113670  0.402
2020 Mamaghani AS, Pedrycz W. Structural optimization of fuzzy rule-based models: Towards efficient complexity management Expert Systems With Applications. 152: 113362. DOI: 10.1016/J.Eswa.2020.113362  0.483
2020 Chen Z, Zhang X, Pedrycz W, Wang X, Skibniewski MJ. Bid evaluation in civil construction under uncertainty: A two-stage LSP-ELECTRE III-based approach Engineering Applications of Artificial Intelligence. 94: 103835. DOI: 10.1016/J.Engappai.2020.103835  0.425
2020 Zhang B, Dong Y, Zhang H, Pedrycz W. Consensus mechanism with maximum-return modifications and minimum-cost feedback: A perspective of game theory European Journal of Operational Research. 287: 546-559. DOI: 10.1016/J.Ejor.2020.04.014  0.304
2020 Du S, Wu M, Chen L, Cao W, Pedrycz W. Operating mode recognition of iron ore sintering process based on the clustering of time series data Control Engineering Practice. 96: 104297. DOI: 10.1016/J.Conengprac.2020.104297  0.317
2020 Chen X, Peng L, Wu Z, Pedrycz W. Controlling the worst consistency index for hesitant fuzzy linguistic preference relations in consensus optimization models Computers & Industrial Engineering. 143: 106423. DOI: 10.1016/J.Cie.2020.106423  0.45
2020 Yu D, Xu Z, Pedrycz W. Bibliometric analysis of rough sets research Applied Soft Computing. 94: 106467. DOI: 10.1016/J.Asoc.2020.106467  0.302
2020 Ghanbari M, Allahviranloo T, Pedrycz W. On the rectangular fuzzy complex linear systems Applied Soft Computing. 91: 106196. DOI: 10.1016/J.Asoc.2020.106196  0.432
2020 Qin J, Xi Y, Pedrycz W. Failure mode and effects analysis (FMEA) for risk assessment based on interval type-2 fuzzy evidential reasoning method Applied Soft Computing. 89: 106134. DOI: 10.1016/J.Asoc.2020.106134  0.31
2020 Tang X, Zhang Q, Peng Z, Pedrycz W, Yang S. Distribution linguistic preference relations with incomplete symbolic proportions for group decision making Applied Soft Computing. 88: 106005. DOI: 10.1016/J.Asoc.2019.106005  0.358
2020 Cabrerizo FJ, Al-Hmouz R, Morfeq A, Martínez MÁ, Pedrycz W, Herrera-Viedma E. Estimating incomplete information in group decision making: A framework of granular computing Applied Soft Computing. 86: 105930. DOI: 10.1016/J.Asoc.2019.105930  0.412
2020 Tang Y, Ren F, Pedrycz W. Fuzzy C-Means clustering through SSIM and patch for image segmentation Applied Soft Computing. 87: 105928. DOI: 10.1016/J.Asoc.2019.105928  0.37
2020 Alfaro-García VG, Merigó JM, Pedrycz W, Monge RG. Citation Analysis of Fuzzy Set Theory Journals: Bibliometric Insights About Authors and Research Areas International Journal of Fuzzy Systems. 1-35. DOI: 10.1007/S40815-020-00924-8  0.322
2020 Balamash A, Pedrycz W, Al-Hmouz R, Morfeq A. Data Description Through Information Granules: A Multiview Perspective International Journal of Fuzzy Systems. 1-17. DOI: 10.1007/S40815-020-00903-Z  0.4
2020 Liu F, Huang M, Huang C, Pedrycz W. Measuring consistency of interval-valued preference relations: comments and comparison Operational Research. 1-29. DOI: 10.1007/S12351-020-00551-Z  0.375
2020 Liu F, Zhang J, Yu Q, Peng Y, Pedrycz W. On weak consistency of interval additive reciprocal matrices Fuzzy Optimization and Decision Making. 19: 153-175. DOI: 10.1007/S10700-020-09314-Z  0.349
2020 Jin J, Ye M, Pedrycz W. Quintuple Implication Principle on interval-valued intuitionistic fuzzy sets Soft Computing. 24: 12091-12109. DOI: 10.1007/s00500-019-04649-1  0.321
2020 Liu P, Xu H, Pedrycz W. A normal wiggly hesitant fuzzy linguistic projection‐based multiattributive border approximation area comparison method International Journal of Intelligent Systems. 35: 432-469. DOI: 10.1002/Int.22213  0.405
2019 Zhu X, Pedrycz W, Li Z. Development and Analysis of Neural Networks Realized in the Presence of Granular Data. Ieee Transactions On Neural Networks and Learning Systems. PMID 31722490 DOI: 10.1109/Tnnls.2019.2945307  0.369
2019 Mencar C, Pedrycz W. GrCount: Counting method for uncertain data. Methodsx. 6: 2455-2459. PMID 31720235 DOI: 10.1016/J.Mex.2019.10.001  0.429
2019 Feng G, Lu W, Pedrycz W, Yang J, Liu X. The Learning of Fuzzy Cognitive Maps With Noisy Data: A Rapid and Robust Learning Method With Maximum Entropy. Ieee Transactions On Cybernetics. PMID 31443065 DOI: 10.1109/Tcyb.2019.2933438  0.326
2019 Lu W, Pedrycz W, Yang J, Liu X. Granular Fuzzy Modeling Guided Through the Synergy of Granulating Output Space and Clustering Input Subspaces. Ieee Transactions On Cybernetics. PMID 31021786 DOI: 10.1109/Tcyb.2019.2909037  0.465
2019 Wu Y, Dong Y, Qin J, Pedrycz W. Flexible Linguistic Expressions and Consensus Reaching With Accurate Constraints in Group Decision-Making. Ieee Transactions On Cybernetics. PMID 30990204 DOI: 10.1109/Tcyb.2019.2906318  0.346
2019 Zhao J, Wang T, Pedrycz W, Wang W. Granular Prediction and Dynamic Scheduling Based on Adaptive Dynamic Programming for the Blast Furnace Gas System. Ieee Transactions On Cybernetics. PMID 30951483 DOI: 10.1109/Tcyb.2019.2901268  0.338
2019 Ouyang T, Pedrycz W, Pizzi NJ. Rule-Based Modeling With DBSCAN-Based Information Granules. Ieee Transactions On Cybernetics. PMID 30908270 DOI: 10.1109/Tcyb.2019.2902603  0.428
2019 Zhu X, Pedrycz W, Li Z. A Development of Granular Input Space in System Modeling. Ieee Transactions On Cybernetics. PMID 30892261 DOI: 10.1109/Tcyb.2019.2899633  0.4
2019 Ouyang T, Pedrycz W, Reyes-Galaviz OF, Pizzi NJ. Granular Description of Data Structures: A Two-Phase Design. Ieee Transactions On Cybernetics. PMID 30605118 DOI: 10.1109/Tcyb.2018.2887115  0.4
2019 Shen Y, Pedrycz W, Wang X. Approximation of Fuzzy Sets by Interval Type-2 Trapezoidal Fuzzy Sets. Ieee Transactions On Cybernetics. PMID 30605116 DOI: 10.1109/Tcyb.2018.2886725  0.493
2019 Karczmarek Pl, Pedrycz W, Kiersztyn A, Dolecki Ml. A comprehensive experimental comparison of the aggregation techniques for face recognition Iranian Journal of Fuzzy Systems. 16: 1-19. DOI: 10.22111/Ijfs.2019.4778  0.312
2019 Kozik R, Pawlicki M, Choraś M, Pedrycz W. Practical Employment of Granular Computing to Complex Application Layer Cyberattack Detection Complexity. 2019: 1-9. DOI: 10.1155/2019/5826737  0.352
2019 Chen H, Cheng R, Pedrycz W, Jin Y. Solving Many-Objective Optimization Problems via Multistage Evolutionary Search Ieee Transactions On Systems, Man, and Cybernetics. 1-13. DOI: 10.1109/Tsmc.2019.2930737  0.326
2019 Ng WWY, Zhang J, Lai CS, Pedrycz W, Lai LL, Wang X. Cost-Sensitive Weighting and Imbalance-Reversed Bagging for Streaming Imbalanced and Concept Drifting in Electricity Pricing Classification Ieee Transactions On Industrial Informatics. 15: 1588-1597. DOI: 10.1109/Tii.2018.2850930  0.332
2019 Xu K, Pedrycz W, Li Z, Nie W. High-Accuracy Signal Subspace Separation Algorithm Based on Gaussian Kernel Soft Partition Ieee Transactions On Industrial Electronics. 66: 491-499. DOI: 10.1109/Tie.2018.2823666  0.308
2019 Zhao J, Chen L, Pedrycz W, Wang W. Variational Inference-Based Automatic Relevance Determination Kernel for Embedded Feature Selection of Noisy Industrial Data Ieee Transactions On Industrial Electronics. 66: 416-428. DOI: 10.1109/Tie.2018.2815997  0.35
2019 Roh S, Oh S, Pedrycz W, Fu Z. Design of Fuzzy Ensemble Architecture Realized with the Aid of FCM-based Fuzzy Partition and NN with Weighted LSE Estimation Ieee Transactions On Fuzzy Systems. 1-1. DOI: 10.1109/Tfuzz.2019.2956903  0.386
2019 Shen Y, Pedrycz W, Chen Y, Wang X, Gacek A. Hyperplane Division in Fuzzy C-Means: Clustering Big Data Ieee Transactions On Fuzzy Systems. 1-1. DOI: 10.1109/Tfuzz.2019.2947231  0.397
2019 Lu W, Feng G, Liu X, Pedrycz W, Zhang L, Yang J. Fast and Effective Learning for Fuzzy Cognitive Maps: A Method Based on Solving Constrained Convex Optimization Problems Ieee Transactions On Fuzzy Systems. 1-1. DOI: 10.1109/Tfuzz.2019.2946119  0.35
2019 Liu X, Jia W, Liu W, Pedrycz W. AFSSE: An Interpretable Classifier with Axiomatic Fuzzy Set and Semantic Entropy Ieee Transactions On Fuzzy Systems. 1-1. DOI: 10.1109/Tfuzz.2019.2945239  0.445
2019 Xu K, Pedrycz W, Li Z, Nie W. Constructing a Virtual Space for Enhancing the Classification Performance of Fuzzy Clustering Ieee Transactions On Fuzzy Systems. 27: 1779-1792. DOI: 10.1109/Tfuzz.2018.2889020  0.436
2019 Lu W, Shan D, Pedrycz W, Zhang L, Yang J, Liu X. Granular Fuzzy Modeling for Multidimensional Numeric Data: A Layered Approach Based on Hyperbox Ieee Transactions On Fuzzy Systems. 27: 775-789. DOI: 10.1109/Tfuzz.2018.2870050  0.488
2019 Zuo H, Lu J, Zhang G, Pedrycz W. Fuzzy Rule-Based Domain Adaptation in Homogeneous and Heterogeneous Spaces Ieee Transactions On Fuzzy Systems. 27: 348-361. DOI: 10.1109/Tfuzz.2018.2853720  0.345
2019 Wang D, Pedrycz W, Li Z. A Two-Phase Development of Fuzzy Rule-Based Model and Their Analysis Ieee Access. 7: 80328-80341. DOI: 10.1109/Access.2019.2919739  0.412
2019 Wang H, Xu C, Xu Z, Zeng X, Pedrycz W. An Aspiration-Based Approach for Qualitative Decision-Making With Complex Linguistic Expressions Ieee Access. 7: 12529-12546. DOI: 10.1109/Access.2019.2892844  0.397
2019 Zhang H, Zhang T, Pedrycz W, Zhao C, Miao D. Improved adaptive image retrieval with the use of shadowed sets Pattern Recognition. 90: 390-403. DOI: 10.1016/J.Patcog.2019.01.029  0.307
2019 Tang Y, Hu X, Pedrycz W, Song X. Possibilistic fuzzy clustering with high-density viewpoint Neurocomputing. 329: 407-423. DOI: 10.1016/J.Neucom.2018.11.007  0.415
2019 Vargas JA, Pedrycz W, Hemerly EM. Improved learning algorithm for two-layer neural networks for identification of nonlinear systems Neurocomputing. 329: 86-96. DOI: 10.1016/J.Neucom.2018.10.008  0.329
2019 Al-Hmouz R, Pedrycz W, Balamash A, Morfeq A. Logic-driven autoencoders Knowledge-Based Systems. 183: 104874. DOI: 10.1016/J.Knosys.2019.104874  0.437
2019 Hu X, Pedrycz W, Wang X. Random ensemble of fuzzy rule-based models Knowledge Based Systems. 181: 104768. DOI: 10.1016/J.Knosys.2019.05.011  0.486
2019 Fu C, Lu W, Pedrycz W, Yang J. Fuzzy granular classification based on the principle of justifiable granularity Knowledge-Based Systems. 170: 89-101. DOI: 10.1016/J.Knosys.2019.02.001  0.487
2019 E H, Cui Y, Pedrycz W, Li Z. Enhancements of rule-based models through refinements of Fuzzy C-Means Knowledge-Based Systems. 170: 43-60. DOI: 10.1016/J.Knosys.2019.01.027  0.506
2019 Ju H, Pedrycz W, Li H, Ding W, Yang X, Zhou X. Sequential three-way classifier with justifiable granularity Knowledge-Based Systems. 163: 103-119. DOI: 10.1016/J.Knosys.2018.08.022  0.425
2019 Ramalho FD, Ekel PY, Pedrycz W, Pereira Júnior JG, Soares GL. Multicriteria decision making under conditions of uncertainty in application to multiobjective allocation of resources Information Fusion. 49: 249-261. DOI: 10.1016/J.Inffus.2018.12.010  0.414
2019 Jing X, Yan Z, Jiang X, Pedrycz W. Network traffic fusion and analysis against DDoS flooding attacks with a novel reversible sketch Information Fusion. 51: 100-113. DOI: 10.1016/J.Inffus.2018.10.013  0.304
2019 Roh S, Oh S, Pedrycz W, Seo K, Fu Z. Design methodology for Radial Basis Function Neural Networks classifier based on locally linear reconstruction and Conditional Fuzzy C-Means clustering International Journal of Approximate Reasoning. 106: 228-243. DOI: 10.1016/J.Ijar.2019.01.008  0.484
2019 Hu X, Pedrycz W, Wang D. Fuzzy rule-based models with randomized development mechanisms Fuzzy Sets and Systems. 361: 71-87. DOI: 10.1016/J.Fss.2018.09.001  0.477
2019 Yao N, Miao D, Pedrycz W, Zhang H, Zhang Z. Causality measures and analysis: A rough set framework Expert Systems With Applications. 136: 187-200. DOI: 10.1016/J.Eswa.2019.06.004  0.369
2019 Mirończuk MM, Protasiewicz J, Pedrycz W. Empirical evaluation of feature projection algorithms for multi-view text classification Expert Systems With Applications. 130: 97-112. DOI: 10.1016/J.Eswa.2019.04.020  0.381
2019 Wang X, Yu F, Pedrycz W, Yu L. Clustering of interval-valued time series of unequal length based on improved dynamic time warping Expert Systems With Applications. 125: 293-304. DOI: 10.1016/J.Eswa.2019.01.005  0.354
2019 Ouyang T, Pedrycz W, Pizzi NJ. Record linkage based on a three-way decision with the use of granular descriptors Expert Systems With Applications. 122: 16-26. DOI: 10.1016/J.Eswa.2018.12.038  0.389
2019 Hu J, Wu M, Chen X, Cao W, Pedrycz W. Multi-model ensemble prediction model for carbon efficiency with application to iron ore sintering process Control Engineering Practice. 88: 141-151. DOI: 10.1016/J.Conengprac.2019.05.009  0.33
2019 Wang L, Wang Y, Pedrycz W. Hesitant 2-tuple linguistic Bonferroni operators and their utilization in group decision making Applied Soft Computing. 77: 653-664. DOI: 10.1016/J.Asoc.2019.01.038  0.36
2019 Song M, Jing Y, Pedrycz W. Granular neural networks: A study of optimizing allocation of information granularity in input space Applied Soft Computing. 77: 67-75. DOI: 10.1016/J.Asoc.2019.01.013  0.617
2019 Soto J, Castillo O, Melin P, Pedrycz W. A New Approach to Multiple Time Series Prediction Using MIMO Fuzzy Aggregation Models with Modular Neural Networks International Journal of Fuzzy Systems. 21: 1629-1648. DOI: 10.1007/S40815-019-00642-W  0.474
2019 Tang X, Zhang Q, Peng Z, Yang S, Pedrycz W. Derivation of personalized numerical scales from distribution linguistic preference relations: an expected consistency-based goal programming approach Neural Computing and Applications. 31: 8769-8786. DOI: 10.1007/S00521-019-04466-5  0.359
2019 Zhou J, Gao C, Pedrycz W, Lai Z, Yue X. Constrained shadowed sets and fast optimization algorithm International Journal of Intelligent Systems. 34: 2655-2675. DOI: 10.1002/Int.22170  0.321
2018 Pratama M, Dimla E, Tjahjowidodo T, Pedrycz W, Lughofer E. Online Tool Condition Monitoring Based on Parsimonious Ensemble. Ieee Transactions On Cybernetics. PMID 30334774 DOI: 10.1109/Tcyb.2018.2871120  0.382
2018 Ding W, Lin CT, Pedrycz W. Multiple Relevant Feature Ensemble Selection Based on Multilayer Co-Evolutionary Consensus MapReduce. Ieee Transactions On Cybernetics. PMID 30130243 DOI: 10.1109/Tcyb.2018.2859342  0.344
2018 Liu F, Pedrycz W, Liu XW. Flexibility Degree of Fuzzy Numbers and Its Implication to a Group-Decision-Making Model. Ieee Transactions On Cybernetics. PMID 30059328 DOI: 10.1109/Tcyb.2018.2853722  0.48
2018 Cimino MGCA, Lazzeri A, Pedrycz W, Vaglini G. Using Stigmergy to Distinguish Event-Specific Topics in Social Discussions. Sensors (Basel, Switzerland). 18. PMID 30004417 DOI: 10.3390/S18072117  0.332
2018 Ng WWY, Tian X, Pedrycz W, Wang X, Yeung DS. Incremental Hash-Bit Learning for Semantic Image Retrieval in Nonstationary Environments. Ieee Transactions On Cybernetics. PMID 29994699 DOI: 10.1109/Tcyb.2018.2846760  0.352
2018 Shen Y, Pedrycz W, Wang X. Clustering Homogeneous Granular Data: Formation and Evaluation. Ieee Transactions On Cybernetics. PMID 29994448 DOI: 10.1109/Tcyb.2018.2802453  0.391
2018 Rong M, Gong D, Zhang Y, Jin Y, Pedrycz W. Multidirectional Prediction Approach for Dynamic Multiobjective Optimization Problems. Ieee Transactions On Cybernetics. PMID 29994141 DOI: 10.1109/Tcyb.2018.2842158  0.336
2018 Zhang Z, Pedrycz W. A Consistency and Consensus-Based Goal Programming Method for Group Decision-Making With Interval-Valued Intuitionistic Multiplicative Preference Relations. Ieee Transactions On Cybernetics. PMID 29994140 DOI: 10.1109/Tcyb.2018.2842073  0.387
2018 Nguyen TT, Pham XC, Liew AW, Pedrycz W. Aggregation of Classifiers: A Justifiable Information Granularity Approach. Ieee Transactions On Cybernetics. PMID 29993920 DOI: 10.1109/Tcyb.2018.2821679  0.429
2018 Kim EH, Oh SK, Pedrycz W. Design of double fuzzy clustering-driven context neural networks. Neural Networks : the Official Journal of the International Neural Network Society. 104: 1-14. PMID 29689457 DOI: 10.1016/J.Neunet.2018.03.018  0.379
2018 Liu C, Pedrycz W, Qian J, Wang M. Covering-based multigranulation decision-theoretic rough set approaches with new strategies Journal of Intelligent & Fuzzy Systems. 35: 1179-1191. DOI: 10.3233/Jifs-18233  0.347
2018 Liu C, Pedrycz W, Jiang F, Wang M. Decision-theoretic rough set approaches to multi-covering approximation spaces based on fuzzy probability measure Journal of Intelligent & Fuzzy Systems. 34: 1917-1931. DOI: 10.3233/Jifs-171275  0.438
2018 Zhao J, Chen L, Pedrycz W, Wang W. A Novel Semi-Supervised Sparse Bayesian Regression Based on Variational Inference for Industrial Datasets With Incomplete Outputs Ieee Transactions On Systems, Man, and Cybernetics. 1-14. DOI: 10.1109/Tsmc.2018.2864752  0.301
2018 Roh S, Oh S, Pedrycz W. Identification of Black Plastics Based on Fuzzy RBF Neural Networks: Focused on Data Preprocessing Techniques Through Fourier Transform Infrared Radiation Ieee Transactions On Industrial Informatics. 14: 1802-1813. DOI: 10.1109/Tii.2017.2771254  0.356
2018 Zhu X, Pedrycz W, Li Z. Granular Models and Granular Outliers Ieee Transactions On Fuzzy Systems. 26: 3835-3846. DOI: 10.1109/Tfuzz.2018.2849736  0.423
2018 Zhang Z, Pedrycz W. Goal Programming Approaches to Managing Consistency and Consensus for Intuitionistic Multiplicative Preference Relations in Group Decision Making Ieee Transactions On Fuzzy Systems. 26: 3261-3275. DOI: 10.1109/Tfuzz.2018.2818074  0.334
2018 Zhu X, Pedrycz W, Li Z. A Design of Granular Takagi–Sugeno Fuzzy Model Through the Synergy of Fuzzy Subspace Clustering and Optimal Allocation of Information Granularity Ieee Transactions On Fuzzy Systems. 26: 2499-2509. DOI: 10.1109/Tfuzz.2018.2813314  0.503
2018 Guo H, Pedrycz W, Liu X. Hidden Markov Models Based Approaches to Long-Term Prediction for Granular Time Series Ieee Transactions On Fuzzy Systems. 26: 2807-2817. DOI: 10.1109/Tfuzz.2018.2802924  0.326
2018 Pratama M, Pedrycz W, Lughofer E. Evolving Ensemble Fuzzy Classifier Ieee Transactions On Fuzzy Systems. 26: 2552-2567. DOI: 10.1109/Tfuzz.2018.2796099  0.356
2018 Liu F, Wu Y, Pedrycz W. A Modified Consensus Model in Group Decision Making With an Allocation of Information Granularity Ieee Transactions On Fuzzy Systems. 26: 3182-3187. DOI: 10.1109/Tfuzz.2018.2793885  0.384
2018 Duan X, Wang Y, Pedrycz W, Liu X, Wang C, Li Z. AFSNN: A Classification Algorithm Using Axiomatic Fuzzy Sets and Neural Networks Ieee Transactions On Fuzzy Systems. 26: 3151-3163. DOI: 10.1109/Tfuzz.2017.2788875  0.444
2018 Kim E, Oh S, Pedrycz W. Design of Reinforced Interval Type-2 Fuzzy C-Means-Based Fuzzy Classifier Ieee Transactions On Fuzzy Systems. 26: 3054-3068. DOI: 10.1109/Tfuzz.2017.2785244  0.456
2018 Zhu X, Pedrycz W, Li Z. Granular Representation of Data: A Design of Families of ϵ-Information Granules Ieee Transactions On Fuzzy Systems. 26: 2107-2119. DOI: 10.1109/Tfuzz.2017.2763122  0.443
2018 Mehlawat MK, Gupta P, Pedrycz W. A New Possibilistic Optimization Model for Multiple Criteria Assignment Problem Ieee Transactions On Fuzzy Systems. 26: 1775-1788. DOI: 10.1109/Tfuzz.2017.2751006  0.389
2018 Zuo H, Zhang G, Pedrycz W, Behbood V, Lu J. Granular Fuzzy Regression Domain Adaptation in Takagi–Sugeno Fuzzy Models Ieee Transactions On Fuzzy Systems. 26: 847-858. DOI: 10.1109/Tfuzz.2017.2694801  0.408
2018 Al-Hmouz R, Pedrycz W, Balamash AS, Morfeq A. Hierarchical System Modeling Ieee Transactions On Fuzzy Systems. 26: 258-269. DOI: 10.1109/Tfuzz.2017.2649581  0.435
2018 Hu Q, Zhang L, Zhou Y, Pedrycz W. Large-Scale Multimodality Attribute Reduction With Multi-Kernel Fuzzy Rough Sets Ieee Transactions On Fuzzy Systems. 26: 226-238. DOI: 10.1109/Tfuzz.2017.2647966  0.515
2018 Segatori A, Marcelloni F, Pedrycz W. On Distributed Fuzzy Decision Trees for Big Data Ieee Transactions On Fuzzy Systems. 26: 174-192. DOI: 10.1109/Tfuzz.2016.2646746  0.479
2018 Shoniker M, Oleynikov O, Cockburn BF, Han J, Rana M, Pedrycz W. Automatic Selection of Process Corner Simulations for Faster Design Verification Ieee Transactions On Computer-Aided Design of Integrated Circuits and Systems. 37: 1312-1316. DOI: 10.1109/Tcad.2017.2748027  0.301
2018 Pedrycz W. Granular computing for data analytics: a manifesto of human-centric computing Ieee/Caa Journal of Automatica Sinica. 5: 1025-1034. DOI: 10.1109/Jas.2018.7511213  0.334
2018 Ren H, Li X, Li Z, Pedrycz W. Data Representation Based on Interval-Sets for Anomaly Detection in Time Series Ieee Access. 6: 27473-27479. DOI: 10.1109/Access.2018.2828864  0.413
2018 Li W, Pedrycz W, Xue X, Zhang X, Fan B, Long B. Information measure of absolute and relative quantification in double-quantitative decision-theoretic rough set model The Journal of Engineering. 2018: 1436-1441. DOI: 10.1049/Joe.2018.8315  0.354
2018 Sheri AM, Rafique MA, Jeon M, Pedrycz W. Background subtraction using Gaussian–Bernoulli restricted Boltzmann machine Iet Image Processing. 12: 1646-1654. DOI: 10.1049/Iet-Ipr.2017.1055  0.33
2018 Ngo LT, Dang TH, Pedrycz W. Towards interval-valued fuzzy set-based collaborative fuzzy clustering algorithms Pattern Recognition. 81: 404-416. DOI: 10.1016/J.Patcog.2018.04.006  0.45
2018 Hu X, Pedrycz W, Wang X. Fuzzy classifiers with information granules in feature space and logic-based computing Pattern Recognition. 80: 156-167. DOI: 10.1016/J.Patcog.2018.03.011  0.5
2018 Loia V, Parente D, Pedrycz W, Tomasiello S. A Granular Functional Network with delay: Some dynamical properties and application to the sign prediction in social networks Neurocomputing. 321: 61-71. DOI: 10.1016/J.Neucom.2018.08.047  0.373
2018 Kim E, Oh S, Pedrycz W. Reinforced hybrid interval fuzzy neural networks architecture: Design and analysis Neurocomputing. 303: 20-36. DOI: 10.1016/J.Neucom.2018.04.003  0.492
2018 Zheng Y, He Y, Xu Z, Pedrycz W. Assessment for hierarchical medical policy proposals using hesitant fuzzy linguistic analytic network process Knowledge-Based Systems. 161: 254-267. DOI: 10.1016/J.Knosys.2018.07.005  0.44
2018 Loia V, Orciuoli F, Pedrycz W. Towards a granular computing approach based on Formal Concept Analysis for discovering periodicities in data Knowledge-Based Systems. 146: 1-11. DOI: 10.1016/J.Knosys.2018.01.032  0.384
2018 Liu F, Yu Q, Pedrycz W, Zhang W. A group decision making model based on an inconsistency index of interval multiplicative reciprocal matrices Knowledge-Based Systems. 145: 67-76. DOI: 10.1016/J.Knosys.2018.01.001  0.388
2018 Zhou X, Xu Z, Yao L, Tu Y, Lev B, Pedrycz W. A novel Data Envelopment Analysis model for evaluating industrial production and environmental management system Journal of Cleaner Production. 170: 773-788. DOI: 10.1016/J.Jclepro.2017.09.160  0.416
2018 Aliev R, Pedrycz W, Huseynov O. Hukuhara difference of Z-numbers Information Sciences. 466: 13-24. DOI: 10.1016/J.Ins.2018.07.033  0.444
2018 Pedrycz W, Krawczak M, Zadrozny S. Computational intelligence techniques for decision support, data mining and information searching Information Sciences. 374-376. DOI: 10.1016/J.Ins.2018.06.053  0.328
2018 Aliev R, Pedrycz W, Huseynov O. Functions defined on a set of Z-numbers Information Sciences. 423: 353-375. DOI: 10.1016/J.Ins.2017.09.056  0.426
2018 Li W, Pedrycz W, Xue X, Xu W, Fan B. Distance-based double-quantitative rough fuzzy sets with logic operations International Journal of Approximate Reasoning. 101: 206-233. DOI: 10.1016/J.Ijar.2018.07.007  0.504
2018 Tang Y, Pedrycz W. On the α ( u , v )-symmetric implicational method for R- and (S, N)-implications International Journal of Approximate Reasoning. 92: 212-231. DOI: 10.1016/J.Ijar.2017.10.009  0.342
2018 Su Y, Liu H, Pedrycz W. A method to construct fuzzy implications–rotation construction International Journal of Approximate Reasoning. 92: 20-31. DOI: 10.1016/J.Ijar.2017.10.003  0.455
2018 Di Martino F, Pedrycz W, Sessa S. Spatiotemporal extended fuzzy C-means clustering algorithm for hotspots detection and prediction Fuzzy Sets and Systems. 340: 109-126. DOI: 10.1016/J.Fss.2017.11.011  0.399
2018 Cabrerizo FJ, Morente-Molinera JA, Pedrycz W, Taghavi A, Herrera-Viedma E. Granulating linguistic information in decision making under consensus and consistency Expert Systems With Applications. 99: 83-92. DOI: 10.1016/J.Eswa.2018.01.030  0.391
2018 Liu S, Pedrycz W, Gacek A, Dai Y. Development of information granules of higher type and their applications to granular models of time series Engineering Applications of Artificial Intelligence. 71: 60-72. DOI: 10.1016/J.Engappai.2018.02.012  0.389
2018 Duan L, Yu F, Pedrycz W, Wang X, Yang X. Time-series clustering based on linear fuzzy information granules Applied Soft Computing. 73: 1053-1067. DOI: 10.1016/J.Asoc.2018.09.032  0.41
2018 Nguyen TT, Nguyen MP, Pham XC, Liew AW, Pedrycz W. Combining heterogeneous classifiers via granular prototypes Applied Soft Computing. 73: 795-815. DOI: 10.1016/J.Asoc.2018.09.021  0.378
2018 Gupta P, Mehlawat MK, Grover N, Pedrycz W. Multi-attribute group decision making based on extended TOPSIS method under interval-valued intuitionistic fuzzy environment Applied Soft Computing. 69: 554-567. DOI: 10.1016/J.Asoc.2018.04.032  0.409
2018 Tang X, Yang S, Pedrycz W. Multiple attribute decision-making approach based on dual hesitant fuzzy Frank aggregation operators Applied Soft Computing. 68: 525-547. DOI: 10.1016/J.Asoc.2018.03.055  0.426
2018 Zhou H, Song M, Pedrycz W. A comparative study of improved GA and PSO in solving multiple traveling salesmen problem Applied Soft Computing. 64: 564-580. DOI: 10.1016/J.Asoc.2017.12.031  0.551
2018 Zhang Z, Pedrycz W, Huang J. Efficient mining product-based fuzzy association rules through central limit theorem Applied Soft Computing. 63: 235-248. DOI: 10.1016/J.Asoc.2017.11.025  0.443
2018 Kolasa M, Długosz R, Talaśka T, Pedrycz W. Efficient methods of initializing neuron weights in self-organizing networks implemented in hardware Applied Mathematics and Computation. 319: 31-47. DOI: 10.1016/J.Amc.2017.01.043  0.315
2018 Karczmarek P, Kiersztyn A, Pedrycz W, Dolecki M. Linguistic Descriptors in Face Recognition International Journal of Fuzzy Systems. 20: 2668-2676. DOI: 10.1007/S40815-018-0517-0  0.321
2018 Li W, Pedrycz W, Xue X, Xu W, Fan B. Fuzziness and incremental information of disjoint regions in double-quantitative decision-theoretic rough set model International Journal of Machine Learning and Cybernetics. 10: 2669-2690. DOI: 10.1007/S13042-018-0893-7  0.433
2018 Bae J, Oh S, Pedrycz W, Fu Z. Design of fuzzy radial basis function neural network classifier based on information data preprocessing for recycling black plastic wastes: comparative studies of ATR FT-IR and Raman spectroscopy Applied Intelligence. 49: 929-949. DOI: 10.1007/S10489-018-1300-5  0.368
2018 Guo H, Pedrycz W, Liu X. Fuzzy time series forecasting based on axiomatic fuzzy set theory Neural Computing and Applications. 31: 3921-3932. DOI: 10.1007/S00521-017-3325-9  0.497
2017 Xu J, Wang G, Li T, Pedrycz W. Local-Density-Based Optimal Granulation and Manifold Information Granule Description. Ieee Transactions On Cybernetics. PMID 28945607 DOI: 10.1109/Tcyb.2017.2750481  0.356
2017 Huang W, Oh SK, Pedrycz W. Hybrid Fuzzy Wavelet Neural Networks Architecture Based on Polynomial Neural Networks and Fuzzy Set/Relation Inference-Based Wavelet Neurons. Ieee Transactions On Neural Networks and Learning Systems. PMID 28809719 DOI: 10.1109/Tnnls.2017.2729589  0.465
2017 Zhang Z, Pedrycz W. Intuitionistic Multiplicative Group Analytic Hierarchy Process and Its Use in Multicriteria Group Decision-Making. Ieee Transactions On Cybernetics. PMID 28727567 DOI: 10.1109/Tcyb.2017.2720167  0.39
2017 Zhang X, Zhuang Y, Wang W, Pedrycz W. Online Feature Transformation Learning for Cross-Domain Object Category Recognition. Ieee Transactions On Neural Networks and Learning Systems. PMID 28613184 DOI: 10.1109/Tnnls.2017.2705113  0.321
2017 Liu C, Pedrycz W, Wang M. Covering-based multigranulation decision-theoretic rough sets Journal of Intelligent & Fuzzy Systems. 32: 749-765. DOI: 10.3233/Jifs-16020  0.351
2017 Liu F, Peng Y, Zhang W, Pedrycz W. On Consistency in AHP and Fuzzy AHP Journal of Systems Science and Information. 5: 128-147. DOI: 10.21078/Jssi-2017-128-20  0.463
2017 Liang D, Pedrycz W, Liu D. Determining Three-Way Decisions With Decision-Theoretic Rough Sets Using a Relative Value Approach Ieee Transactions On Systems, Man, and Cybernetics: Systems. 47: 1785-1799. DOI: 10.1109/Tsmc.2016.2531644  0.356
2017 Zuo H, Zhang G, Pedrycz W, Behbood V, Lu J. Fuzzy Regression Transfer Learning in Takagi–Sugeno Fuzzy Models Ieee Transactions On Fuzzy Systems. 25: 1795-1807. DOI: 10.1109/Tfuzz.2016.2633376  0.384
2017 Zhu X, Pedrycz W, Li Z. Granular Encoders and Decoders: A Study in Processing Information Granules Ieee Transactions On Fuzzy Systems. 25: 1115-1126. DOI: 10.1109/Tfuzz.2016.2598366  0.454
2017 Zhang Z, Pedrycz W. Models of Mathematical Programming for Intuitionistic Multiplicative Preference Relations Ieee Transactions On Fuzzy Systems. 25: 945-957. DOI: 10.1109/Tfuzz.2016.2587326  0.427
2017 Zhao J, Sheng C, Wang W, Pedrycz W, Liu Q. Data-Based Predictive Optimization for Byproduct Gas System in Steel Industry Ieee Transactions On Automation Science and Engineering. 14: 1761-1770. DOI: 10.1109/Tase.2016.2629505  0.359
2017 Abdolrazzaghi M, Zarifi MH, Pedrycz W, Daneshmand M. Robust Ultra-High Resolution Microwave Planar Sensor Using Fuzzy Neural Network Approach Ieee Sensors Journal. 17: 323-332. DOI: 10.1109/Jsen.2016.2631618  0.369
2017 Liu S, Pedrycz W, Gacek A, Dai Y. A two-phase method of forming a granular representation of signals Signal Processing. 141: 1-15. DOI: 10.1016/J.Sigpro.2017.05.026  0.377
2017 Pedrycz W. Selected insights into building data associations and their granular augmentations Procedia Computer Science. 120: 4. DOI: 10.1016/J.Procs.2017.11.200  0.331
2017 Li F, Miao D, Pedrycz W. Granular multi-label feature selection based on mutual information Pattern Recognition. 67: 410-423. DOI: 10.1016/J.Patcog.2017.02.025  0.328
2017 Li T, Zhang L, Lu W, Hou H, Liu X, Pedrycz W, Zhong C. Interval kernel Fuzzy C-Means clustering of incomplete data Neurocomputing. 237: 316-331. DOI: 10.1016/J.Neucom.2017.01.017  0.397
2017 Hu X, Pedrycz W, Wang X. Development of granular models through the design of a granular output spaces Knowledge-Based Systems. 134: 159-171. DOI: 10.1016/J.Knosys.2017.07.030  0.375
2017 Ren H, Liu M, Li Z, Pedrycz W. A Piecewise Aggregate pattern representation approach for anomaly detection in time series Knowledge-Based Systems. 135: 29-39. DOI: 10.1016/J.Knosys.2017.07.021  0.353
2017 Truong HQ, Ngo LT, Pedrycz W. Granular Fuzzy Possibilistic C-Means Clustering approach to DNA microarray problem Knowledge-Based Systems. 133: 53-65. DOI: 10.1016/J.Knosys.2017.06.019  0.405
2017 Hu X, Pedrycz W, Wang X. From fuzzy rule-based models to their granular generalizations Knowledge-Based Systems. 124: 133-143. DOI: 10.1016/J.Knosys.2017.03.007  0.505
2017 Kim E, Oh S, Pedrycz W. Reinforced rule-based fuzzy models: Design and analysis Knowledge-Based Systems. 119: 44-58. DOI: 10.1016/J.Knosys.2016.12.003  0.498
2017 Wang H, Xu Z, Pedrycz W. An overview on the roles of fuzzy set techniques in big data processing: Trends, challenges and opportunities Knowledge-Based Systems. 118: 15-30. DOI: 10.1016/J.Knosys.2016.11.008  0.477
2017 Froelich W, Pedrycz W. Fuzzy cognitive maps in the modeling of granular time series Knowledge-Based Systems. 115: 110-122. DOI: 10.1016/J.Knosys.2016.10.017  0.468
2017 Qian Y, Cheng H, Wang J, Liang J, Pedrycz W, Dang C. Grouping granular structures in human granulation intelligence Information Sciences. 382: 150-169. DOI: 10.1016/J.Ins.2016.11.024  0.328
2017 Yan Z, Jing X, Pedrycz W. Fusing and mining opinions for reputation generation Information Fusion. 36: 172-184. DOI: 10.1016/J.Inffus.2016.11.011  0.339
2017 Zhang L, Zhong W, Zhong C, Lu W, Liu X, Pedrycz W. Fuzzy C-Means clustering based on dual expression between cluster prototypes and reconstructed data International Journal of Approximate Reasoning. 90: 389-410. DOI: 10.1016/J.Ijar.2017.08.008  0.375
2017 Su Y, Liu H, Pedrycz W. Coimplications derived from pseudo-uninorms on a complete lattice International Journal of Approximate Reasoning. 90: 107-119. DOI: 10.1016/J.Ijar.2017.07.006  0.396
2017 Shen Y, Pedrycz W. Collaborative fuzzy clustering algorithm: Some refinements International Journal of Approximate Reasoning. 86: 41-61. DOI: 10.1016/J.Ijar.2017.04.004  0.426
2017 Balamash A, Pedrycz W, Al-Hmouz R, Morfeq A. Perspective-oriented data analysis through the development of information granules of order 2 International Journal of Approximate Reasoning. 85: 97-106. DOI: 10.1016/J.Ijar.2017.03.006  0.426
2017 Yang X, Yu F, Pedrycz W. Long-term forecasting of time series based on linear fuzzy information granules and fuzzy inference system International Journal of Approximate Reasoning. 81: 1-27. DOI: 10.1016/J.Ijar.2016.10.010  0.466
2017 Liu F, Pedrycz W, Wang Z, Zhang W. An axiomatic approach to approximation-consistency of triangular fuzzy reciprocal preference relations Fuzzy Sets and Systems. 322: 1-18. DOI: 10.1016/J.Fss.2017.02.004  0.413
2017 Reyes-Galaviz OF, Pedrycz W. Enhancement of the classification and reconstruction performance of fuzzy C-means with refinements of prototypes Fuzzy Sets and Systems. 318: 80-99. DOI: 10.1016/J.Fss.2016.07.002  0.461
2017 Zhou X, Yu N, Tu Y, Pedrycz W, Lev B. Bi-level plant selection and production allocation model under type-2 fuzzy demand Expert Systems With Applications. 86: 87-98. DOI: 10.1016/J.Eswa.2017.05.057  0.427
2017 Vo B, Le T, Pedrycz W, Nguyen G, Baik SW. Mining erasable itemsets with subset and superset itemset constraints Expert Systems With Applications. 69: 50-61. DOI: 10.1016/J.Eswa.2016.10.028  0.329
2017 Zhang Z, Pedrycz W, Huang J. Efficient frequent itemsets mining through sampling and information granulation Engineering Applications of Artificial Intelligence. 65: 119-136. DOI: 10.1016/J.Engappai.2017.07.016  0.342
2017 Qin J, Liu X, Pedrycz W. An extended TODIM multi-criteria group decision making method for green supplier selection in interval type-2 fuzzy environment European Journal of Operational Research. 258: 626-638. DOI: 10.1016/J.Ejor.2016.09.059  0.429
2017 Świetlicka A, Gugała K, Pedrycz W, Rybarczyk A. Development of the deterministic and stochastic Markovian model of a dendritic neuron Biocybernetics and Biomedical Engineering. 37: 201-216. DOI: 10.1016/J.Bbe.2016.10.002  0.31
2017 Wu G, Pedrycz W, Suganthan P, Li H. Using variable reduction strategy to accelerate evolutionary optimization Applied Soft Computing. 61: 283-293. DOI: 10.1016/J.Asoc.2017.08.012  0.304
2017 Zhu X, Pedrycz W, Li Z. Fuzzy clustering with nonlinearly transformed data Applied Soft Computing. 61: 364-376. DOI: 10.1016/J.Asoc.2017.07.026  0.42
2017 Li J, Pedrycz W, Jamal I. Multivariate time series anomaly detection: A framework of Hidden Markov Models Applied Soft Computing. 60: 229-240. DOI: 10.1016/J.Asoc.2017.06.035  0.376
2017 Machado-Coelho T, Machado A, Jaulin L, Ekel P, Pedrycz W, Soares G. An interval space reducing method for constrained problems with particle swarm optimization Applied Soft Computing. 59: 405-417. DOI: 10.1016/J.Asoc.2017.05.022  0.346
2017 Hu X, Pedrycz W, Wu G, Wang X. Data reconstruction with information granules: An augmented method of fuzzy clustering Applied Soft Computing. 55: 523-532. DOI: 10.1016/J.Asoc.2017.02.014  0.457
2017 Karczmarek P, Kiersztyn A, Pedrycz W. Generalized Choquet Integral for Face Recognition International Journal of Fuzzy Systems. 20: 1047-1055. DOI: 10.1007/S40815-017-0355-5  0.33
2017 Al-Hmouz R, Pedrycz W, Daqrouq K, Morfeq A. Development of Multimodal Biometric Systems with Three-Way and Fuzzy Set-Based Decision Mechanisms International Journal of Fuzzy Systems. 20: 128-140. DOI: 10.1007/S40815-017-0299-9  0.361
2016 Wang S, Pedrycz W. Data-Driven Adaptive Probabilistic Robust Optimization Using Information Granulation. Ieee Transactions On Cybernetics. PMID 28026796 DOI: 10.1109/Tcyb.2016.2638461  0.391
2016 Zhang X, Zhuang Y, Wang W, Pedrycz W. Transfer Boosting With Synthetic Instances for Class Imbalanced Object Recognition. Ieee Transactions On Cybernetics. PMID 28026795 DOI: 10.1109/Tcyb.2016.2636370  0.329
2016 Zhu X, Pedrycz W, Li Z. Granular Data Description: Designing Ellipsoidal Information Granules. Ieee Transactions On Cybernetics. PMID 27740507 DOI: 10.1109/TCYB.2016.2612226  0.352
2016 Liu F, Pedrycz W, Zhang WG. Limited Rationality and Its Quantification Through the Interval Number Judgments With Permutations. Ieee Transactions On Cybernetics. PMID 27542190 DOI: 10.1109/Tcyb.2016.2594491  0.417
2016 Zhou N, Cheng H, Pedrycz W, Zhang Y, Liu H. Discriminative sparse subspace learning and its application to unsupervised feature selection. Isa Transactions. PMID 26803552 DOI: 10.1016/J.Isatra.2015.12.011  0.349
2016 Su SF, Pedrycz W, Hong TP, De Carvalho Fde A. Guest Editorial Special Issue on Granular/Symbolic Data Processing. Ieee Transactions On Cybernetics. 46: 342-3. PMID 26742157 DOI: 10.1109/Tcyb.2015.2513258  0.426
2016 Zjavka L, Pedrycz W. Constructing general partial differential equations using polynomial and neural networks. Neural Networks : the Official Journal of the International Neural Network Society. 73: 58-69. PMID 26547244 DOI: 10.1016/J.Neunet.2015.10.001  0.337
2016 Zhao J, Han Z, Pedrycz W, Wang W. Granular Model of Long-Term Prediction for Energy System in Steel Industry. Ieee Transactions On Cybernetics. 46: 388-400. PMID 26168454 DOI: 10.1109/Tcyb.2015.2445918  0.332
2016 Talaska T, Kolasa M, Dlugosz R, Pedrycz W. Analog Programmable Distance Calculation Circuit for Winner Takes All Neural Network Realized in the CMOS Technology. Ieee Transactions On Neural Networks and Learning Systems. 27: 661-73. PMID 26087501 DOI: 10.1109/Tnnls.2015.2434847  0.307
2016 Li F, Zheng D, Zhao T, Pedrycz W. A novel approach for anomaly detection in data streams: Fuzzy-statistical detection mode Journal of Intelligent and Fuzzy Systems. 30: 2611-2622. DOI: 10.3233/Ifs-151910  0.42
2016 Liu C, Pedrycz W. Covering-based multi-granulation fuzzy rough sets Journal of Intelligent and Fuzzy Systems. 30: 303-318. DOI: 10.3233/Ifs-151757  0.477
2016 Pedrycz W. System Modeling With Fuzzy Models: Fundamental Developments And Perspectives Iranian Journal of Fuzzy Systems. 13: 1-14. DOI: 10.22111/Ijfs.2016.2940  0.432
2016 Wang Y, Dai Y, Chen YW, Pedrycz W. An interpretability-accuracy tradeoff in learning parameters of intuitionistic fuzzy rule-based systems Journal of Advanced Computational Intelligence and Intelligent Informatics. 20: 773-787. DOI: 10.20965/Jaciii.2016.P0773  0.359
2016 Homenda W, Jastrzebska A, Pedrycz W. Fuzzy cognitive map reconstruction: Dynamics versus history Applied Mathematics and Information Sciences. 10: 93-105. DOI: 10.18576/Amis/100109  0.359
2016 Homenda W, Pedrycz W. Automatic data understanding: The tool for intelligent man-machine communication Applied Mathematics and Information Sciences. 10: 49-61. DOI: 10.18576/Amis/100105  0.316
2016 Aliev RA, Pedrycz W, Huseynov OH, Eyupoglu SZ. Approximate Reasoning on a Basis of Z-number valued If-Then Rules Ieee Transactions On Fuzzy Systems. DOI: 10.1109/Tfuzz.2016.2612303  0.452
2016 Hu X, Pedrycz W, Wang X. Granular Fuzzy Rule-based Models: A Study in a Comprehensive Evaluation of Fuzzy Models Ieee Transactions On Fuzzy Systems. DOI: 10.1109/Tfuzz.2016.2612300  0.485
2016 Huang W, Oh SK, Pedrycz W. Fuzzy Wavelet Polynomial Neural Networks: Analysis and Design Ieee Transactions On Fuzzy Systems. DOI: 10.1109/Tfuzz.2016.2612267  0.458
2016 Zhou J, Li X, Pedrycz W. Mean-Semi-Entropy Models of Fuzzy Portfolio Selection Ieee Transactions On Fuzzy Systems. 24: 1627-1636. DOI: 10.1109/Tfuzz.2016.2543753  0.473
2016 Livi L, Tahayori H, Rizzi A, Sadeghian A, Pedrycz W. Classification of type-2 fuzzy sets represented as sequences of vertical slices Ieee Transactions On Fuzzy Systems. 24: 1022-1034. DOI: 10.1109/Tfuzz.2015.2500274  0.439
2016 Pedrycz W, Wang X. Designing Fuzzy Sets With the Use of the Parametric Principle of Justifiable Granularity Ieee Transactions On Fuzzy Systems. 24: 489-496. DOI: 10.1109/Tfuzz.2015.2453393  0.405
2016 Pedrycz W, Jastrzebska A, Homenda W. Design of fuzzy cognitive maps for modeling time series Ieee Transactions On Fuzzy Systems. 24: 120-130. DOI: 10.1109/Tfuzz.2015.2428717  0.387
2016 Espin-Andrade RA, Gonzalez E, Pedrycz W, Fernandez E. An Interpretable Logical Theory: The case of Compensatory Fuzzy Logic International Journal of Computational Intelligence Systems. 9: 612-626. DOI: 10.1080/18756891.2016.1204111  0.317
2016 Pedrycz W. From Fuzzy Models to Granular Fuzzy Models International Journal of Computational Intelligence Systems. 9: 35-42. DOI: 10.1080/18756891.2016.1180818  0.442
2016 Qin J, Liu X, Pedrycz W. Multi-attribute group decision making based on Choquet integral under interval-valued intuitionistic fuzzy environment International Journal of Computational Intelligence Systems. 9: 133-152. DOI: 10.1080/18756891.2016.1146530  0.456
2016 Hu J, Pedrycz W, Wang G. A roughness measure of fuzzy sets from the perspective of distance International Journal of General Systems. 1-16. DOI: 10.1080/03081079.2015.1086580  0.424
2016 Oh SK, Kim WD, Pedrycz W. Design of radial basis function neural network classifier realized with the aid of data preprocessing techniques: Design and analysis International Journal of General Systems. 45: 434-454. DOI: 10.1080/03081079.2015.1072523  0.471
2016 Cabrerizo FJ, Pedrycz W, Pérez IJ, Alonso S, Herrera-Viedma E. Group Decision Making in Linguistic Contexts: An Information Granulation Approach Procedia Computer Science. 91: 715-724. DOI: 10.1016/J.Procs.2016.07.062  0.354
2016 Fan K, Pedrycz W. Opinion evolution influenced by informed agents Physica a: Statistical Mechanics and Its Applications. 462: 431-441. DOI: 10.1016/J.Physa.2016.06.110  0.332
2016 Ng WW, Zeng G, Zhang J, Yeung DS, Pedrycz W. Dual autoencoders features for imbalance classification problem Pattern Recognition. 60: 875-889. DOI: 10.1016/J.Patcog.2016.06.013  0.346
2016 Zhong C, Pedrycz W, Li Z, Wang D, Li L. Fuzzy associative memories: A design through fuzzy clustering Neurocomputing. 173: 1154-1162. DOI: 10.1016/J.Neucom.2015.08.072  0.406
2016 Feng F, Cho J, Pedrycz W, Fujita H, Herawan T. Soft set based association rule mining Knowledge-Based Systems. 111: 268-282. DOI: 10.1016/J.Knosys.2016.08.020  0.377
2016 Pham VN, Ngo LT, Pedrycz W. Interval-valued fuzzy set approach to fuzzy co-clustering for data classification Knowledge-Based Systems. 107: 1-13. DOI: 10.1016/J.Knosys.2016.05.049  0.442
2016 Protasiewicz J, Pedrycz W, Kozłowski M, Dadas S, Stanisławek T, Kopacz A, Gałȩzewska M. A recommender system of reviewers and experts in reviewing problems Knowledge-Based Systems. 106: 164-178. DOI: 10.1016/J.Knosys.2016.05.041  0.419
2016 Nguyen D, Nguyen LTT, Vo B, Pedrycz W. Efficient mining of class association rules with the itemset constraint Knowledge-Based Systems. 103: 73-88. DOI: 10.1016/J.Knosys.2016.03.025  0.4
2016 Wang X, Pedrycz W, Gacek A, Liu X. From numeric data to information granules: A design through clustering and the principle of justifiable granularity Knowledge-Based Systems. 101: 100-113. DOI: 10.1016/J.Knosys.2016.03.012  0.421
2016 Zhang L, Lu W, Liu X, Pedrycz W, Zhong C. Fuzzy C-Means clustering of incomplete data based on probabilistic information granules of missing values Knowledge-Based Systems. 99: 51-70. DOI: 10.1016/J.Knosys.2016.01.048  0.438
2016 Hu J, Pedrycz W, Wang G, Wang K. Rough sets in distributed decision information systems Knowledge-Based Systems. 94: 13-22. DOI: 10.1016/J.Knosys.2015.10.025  0.345
2016 Ekel P, Kokshenev I, Parreiras R, Pedrycz W, Pereira J. Multiobjective and multiattribute decision making in a fuzzy environment and their power engineering applications Information Sciences. 361: 100-119. DOI: 10.1016/J.Ins.2016.04.030  0.406
2016 Lei X, Wang F, Wu FX, Zhang A, Pedrycz W. Protein complex identification through Markov clustering with firefly algorithm on dynamic protein-protein interaction networks Information Sciences. 329: 303-316. DOI: 10.1016/J.Ins.2015.09.028  0.339
2016 Aliev RA, Pedrycz W, Kreinovich V, Huseynov OH. The general theory of decisions Information Sciences. 327: 125-148. DOI: 10.1016/J.Ins.2015.07.055  0.338
2016 Roh SB, Oh SK, Pedrycz W, Seo K. Development of autofocusing algorithm based on fuzzy transforms Fuzzy Sets and Systems. 288: 129-144. DOI: 10.1016/J.Fss.2015.08.029  0.368
2016 Kerr-Wilson J, Pedrycz W. Design of rule-based models through information granulation Expert Systems With Applications. 46: 274-285. DOI: 10.1016/J.Eswa.2015.10.030  0.453
2016 Ouyang Y, Pedrycz W. A new model for intuitionistic fuzzy multi-attributes decision making European Journal of Operational Research. 249: 677-682. DOI: 10.1016/J.Ejor.2015.08.043  0.456
2016 Zhong C, Pedrycz W, Wang D, Li L, Li Z. Granular data imputation: A framework of Granular Computing Applied Soft Computing Journal. 46: 307-316. DOI: 10.1016/J.Asoc.2016.05.006  0.463
2016 Zhou X, Pedrycz W, Kuang Y, Zhang Z. Type-2 fuzzy multi-objective DEA model: An application to sustainable supplier evaluation Applied Soft Computing Journal. 46: 424-440. DOI: 10.1016/J.Asoc.2016.04.038  0.45
2016 Hu X, Pedrycz W, Wang X. Optimal allocation of information granularity in system modeling through the maximization of information specificity: A development of granular input space Applied Soft Computing Journal. 42: 410-422. DOI: 10.1016/J.Asoc.2016.02.001  0.484
2016 Lu W, Zhang L, Pedrycz W, Yang J, Liu X. The granular extension of Sugeno-type fuzzy models based on optimal allocation of information granularity and its application to forecasting of time series Applied Soft Computing Journal. 42: 38-52. DOI: 10.1016/J.Asoc.2016.01.021  0.435
2016 Qin J, Liu X, Pedrycz W. Frank aggregation operators and their application to hesitant fuzzy multiple attribute decision making Applied Soft Computing Journal. 41: 428-452. DOI: 10.1016/J.Asoc.2015.12.030  0.395
2016 Homenda W, Jastrzebska A, Pedrycz W. Multicriteria decision making inspired by human cognitive processes Applied Mathematics and Computation. 290: 392-411. DOI: 10.1016/J.Amc.2016.05.041  0.376
2016 Huang W, Oh SK, Pedrycz W. Hybrid fuzzy polynomial neural networks with the aid of weighted fuzzy clustering method and fuzzy polynomial neurons Applied Intelligence. 1-22. DOI: 10.1007/S10489-016-0844-5  0.492
2016 Nguyen H, Vo B, Nguyen M, Pedrycz W. An efficient algorithm for mining frequent weighted itemsets using interval word segments Applied Intelligence. 1-13. DOI: 10.1007/S10489-016-0799-6  0.327
2016 Al-Hmouz R, Pedrycz W. Models of time series with time granulation Knowledge and Information Systems. 48: 561-580. DOI: 10.1007/S10115-015-0868-X  0.358
2016 Al-Hmouz R, Pedrycz W, Balamash AS, Morfeq A. Granular description of data in a non-stationary environment Soft Computing. 1-18. DOI: 10.1007/s00500-016-2352-2  0.343
2016 Isazadeh A, Mahan F, Pedrycz W. MFlexDT: multi flexible fuzzy decision tree for data stream classification Soft Computing. 20: 3719-3733. DOI: 10.1007/s00500-015-1733-2  0.305
2016 Wei Y, Watada J, Pedrycz W. Design of a qualitative classification model through fuzzy support vector machine with type-2 fuzzy expected regression classifier preset Ieej Transactions On Electrical and Electronic Engineering. 11: 348-356. DOI: 10.1002/Tee.22224  0.482
2016 Zhang L, Lu W, Liu X, Pedrycz W, Zhong C, Wang L. A Global Clustering Approach Using Hybrid Optimization for Incomplete Data Based on Interval Reconstruction of Missing Value International Journal of Intelligent Systems. 31: 297-313. DOI: 10.1002/Int.21752  0.39
2015 An S, Hu Q, Pedrycz W, Zhu P, Tsang EC. Data-Distribution-Aware Fuzzy Rough Set Model and its Application to Robust Classification. Ieee Transactions On Cybernetics. PMID 26584507 DOI: 10.1109/Tcyb.2015.2496425  0.464
2015 Yoo SH, Oh SK, Pedrycz W. Optimized face recognition algorithm using radial basis function neural networks and its practical applications. Neural Networks : the Official Journal of the International Neural Network Society. 69: 111-25. PMID 26163042 DOI: 10.1016/J.Neunet.2015.05.001  0.454
2015 Ding Y, Cheng L, Pedrycz W, Hao K. Global Nonlinear Kernel Prediction for Large Data Set With a Particle Swarm-Optimized Interval Support Vector Regression. Ieee Transactions On Neural Networks and Learning Systems. PMID 25974954 DOI: 10.1109/Tnnls.2015.2426182  0.408
2015 Livi L, Sadeghian A, Pedrycz W. Entropic One-Class Classifiers. Ieee Transactions On Neural Networks and Learning Systems. 26: 3187-200. PMID 25879977 DOI: 10.1109/Tnnls.2015.2418332  0.405
2015 Chalmers E, Pedrycz W, Lou E. Human experts' and a fuzzy model's predictions of outcomes of scoliosis treatment: a comparative analysis. Ieee Transactions On Bio-Medical Engineering. 62: 1001-7. PMID 25494498 DOI: 10.1109/Tbme.2014.2377594  0.31
2015 Pedrycz W. Concepts and Design Aspects of Granular Models of Type-1 and Type-2 The International Journal of Fuzzy Logic and Intelligent Systems. 15: 87-95. DOI: 10.5391/Ijfis.2015.15.2.87  0.398
2015 Pedrycz W. Granular fuzzy rule-based architectures: Pursuing analysis and design in the framework of granular computing Intelligent Decision Technologies. 9: 321-330. DOI: 10.3233/Idt-140227  0.473
2015 Acampora G, Pedrycz W, Vitiello A. A Competent Memetic Algorithm for Learning Fuzzy Cognitive Maps Ieee Transactions On Fuzzy Systems. 23: 2397-2411. DOI: 10.1109/Tfuzz.2015.2426311  0.401
2015 Pedrycz W, Al-Hmouz R, Balamash AS, Morfeq A. Hierarchical Granular Clustering: An Emergence of Information Granules of Higher Type and Higher Order Ieee Transactions On Fuzzy Systems. 23: 2270-2283. DOI: 10.1109/Tfuzz.2015.2417896  0.486
2015 Behbood V, Lu J, Zhang G, Pedrycz W. Multistep Fuzzy Bridged Refinement Domain Adaptation Algorithm and Its Application to Bank Failure Prediction Ieee Transactions On Fuzzy Systems. 23: 1917-1935. DOI: 10.1109/Tfuzz.2014.2387872  0.39
2015 Wang XZ, Xing HJ, Li Y, Hua Q, Dong CR, Pedrycz W. A Study on Relationship Between Generalization Abilities and Fuzziness of Base Classifiers in Ensemble Learning Ieee Transactions On Fuzzy Systems. 23: 1638-1654. DOI: 10.1109/Tfuzz.2014.2371479  0.445
2015 Wang S, Pedrycz W. Robust Granular Optimization: A Structured Approach for Optimization under Integrated Uncertainty Ieee Transactions On Fuzzy Systems. 23: 1372-1386. DOI: 10.1109/Tfuzz.2014.2360941  0.351
2015 Gacek A, Pedrycz W. Clustering Granular Data and Their Characterization with Information Granules of Higher Type Ieee Transactions On Fuzzy Systems. 23: 850-860. DOI: 10.1109/Tfuzz.2014.2329707  0.345
2015 Qin J, Chu J, Liu X, Pedrycz W. Approaches to interval type-2 fuzzy multiple attribute group decision making based on grey incidence analysis and FTP utility function Ieee International Conference On Fuzzy Systems. 2015. DOI: 10.1109/FUZZ-IEEE.2015.7337823  0.368
2015 Espin-Andrade RA, Caballero EG, Pedrycz W, Fernández González ER. Archimedean-Compensatory Fuzzy Logic Systems International Journal of Computational Intelligence Systems. 8: 54-62. DOI: 10.1080/18756891.2015.1129591  0.445
2015 Pedrycz W, Gacek A, Wang X. Clustering in augmented space of granular constraints: A study in knowledge-based clustering Pattern Recognition Letters. 67: 122-129. DOI: 10.1016/J.Patrec.2015.08.019  0.41
2015 Zhou N, Xu Y, Cheng H, Fang J, Pedrycz W. Global and local structure preserving sparse subspace learning: An iterative approach to unsupervised feature selection Pattern Recognition. DOI: 10.1016/J.Patcog.2015.12.008  0.36
2015 Wang S, Pedrycz W, Zhu Q, Zhu W. Subspace learning for unsupervised feature selection via matrix factorization Pattern Recognition. 48: 10-19. DOI: 10.1016/J.Patcog.2014.08.004  0.343
2015 Wang X, Liu X, Pedrycz W, Zhang L. Fuzzy rule based decision trees Pattern Recognition. 48: 50-59. DOI: 10.1016/J.Patcog.2014.08.001  0.423
2015 Reyes-Galaviz OF, Pedrycz W. Granular fuzzy modeling with evolving hyperboxes in multi-dimensional space of numerical data Neurocomputing. 168: 240-253. DOI: 10.1016/J.Neucom.2015.05.102  0.486
2015 Qin J, Liu X, Pedrycz W. An extended VIKOR method based on prospect theory for multiple attribute decision making under interval type-2 fuzzy environment Knowledge-Based Systems. 86: 116-130. DOI: 10.1016/J.Knosys.2015.05.025  0.467
2015 Pedrycz W, Succi G, Sillitti A, Iljazi J. Data description: A general framework of information granules Knowledge-Based Systems. 80: 98-108. DOI: 10.1016/J.Knosys.2014.12.030  0.417
2015 Pedrycz W, Al-Hmouz R, Balamash AS, Morfeq A. Designing granular fuzzy models: A hierarchical approach to fuzzy modeling Knowledge-Based Systems. 76: 42-52. DOI: 10.1016/J.Knosys.2014.11.025  0.473
2015 Wang S, Pedrycz W, Zhu Q, Zhu W. Unsupervised feature selection via maximum projection and minimum redundancy Knowledge-Based Systems. 75: 19-29. DOI: 10.1016/J.Knosys.2014.11.008  0.366
2015 Dong R, Pedrycz W. Approximation grid evaluation-based PID control in cascade with nonlinear gain Journal of the Franklin Institute. 352: 4279-4296. DOI: 10.1016/J.Jfranklin.2015.06.018  0.307
2015 Li J, Pedrycz W, Wang X. A rule-based development of incremental models International Journal of Approximate Reasoning. 64: 20-38. DOI: 10.1016/J.Ijar.2015.06.007  0.486
2015 Reyes-Galaviz OF, Pedrycz W. Granular fuzzy models: Analysis, design, and evaluation International Journal of Approximate Reasoning. 64: 1-19. DOI: 10.1016/J.Ijar.2015.06.005  0.462
2015 Lu W, Chen X, Pedrycz W, Liu X, Yang J. Using interval information granules to improve forecasting in fuzzy time series International Journal of Approximate Reasoning. 57: 1-18. DOI: 10.1016/J.Ijar.2014.11.002  0.435
2015 Nguyen DD, Ngo LT, Pham LT, Pedrycz W. Towards hybrid clustering approach to data classification: Multiple kernels based interval-valued Fuzzy C-Means algorithms Fuzzy Sets and Systems. 279: 17-39. DOI: 10.1016/J.Fss.2015.01.020  0.487
2015 Portmann E, Meier A, Cudré-Mauroux P, Pedrycz W. FORA - A fuzzy set based framework for online reputation management Fuzzy Sets and Systems. 269: 90-114. DOI: 10.1016/J.Fss.2014.06.004  0.453
2015 Pedrycz W. From Numeric Models to Granular System Modeling Fuzzy Information and Engineering. 7: 1-13. DOI: 10.1016/J.Fiae.2015.03.001  0.399
2015 Al-Hmouz R, Pedrycz W, Balamash A. Description and prediction of time series: A general framework of Granular Computing Expert Systems With Applications. 42: 4830-4839. DOI: 10.1016/J.Eswa.2015.01.060  0.349
2015 Balamash A, Pedrycz W, Al-Hmouz R, Morfeq A. An expansion of fuzzy information granules through successive refinements of their information content and their use to system modeling Expert Systems With Applications. 42: 2985-2997. DOI: 10.1016/J.Eswa.2014.11.027  0.432
2015 Chen J, Pedrycz W, Ha M, Ma L. Set-valued samples based support vector regression and its applications Expert Systems With Applications. 42: 2502-2509. DOI: 10.1016/J.Eswa.2014.09.038  0.351
2015 Wang W, Pedrycz W, Liu X. Time series long-term forecasting model based on information granules and fuzzy clustering Engineering Applications of Artificial Intelligence. 41: 17-24. DOI: 10.1016/J.Engappai.2015.01.006  0.409
2015 Izakian H, Pedrycz W, Jamal I. Fuzzy clustering of time series data using dynamic time warping distance Engineering Applications of Artificial Intelligence. 39: 235-244. DOI: 10.1016/J.Engappai.2014.12.015  0.411
2015 Sheri AM, Rafique A, Pedrycz W, Jeon M. Contrastive divergence for memristor-based restricted Boltzmann machine Engineering Applications of Artificial Intelligence. 37: 336-342. DOI: 10.1016/J.Engappai.2014.09.013  0.303
2015 Ngo LT, Mai DS, Pedrycz W. Semi-supervising Interval Type-2 Fuzzy C-Means clustering with spatial information for multi-spectral satellite image classification and change detection Computers and Geosciences. 83: 1-16. DOI: 10.1016/J.Cageo.2015.06.011  0.414
2015 Wu G, Pedrycz W, Suganthan PN, Mallipeddi R. A variable reduction strategy for evolutionary algorithms handling equality constraints Applied Soft Computing Journal. 37: 774-786. DOI: 10.1016/J.Asoc.2015.09.007  0.326
2015 Giacomin PAS, Hemerly EM, Pedrycz W. A probabilistic approach for designing nonlinear optimal robust tracking controllers for unmanned aerial vehicles Applied Soft Computing Journal. 34: 26-38. DOI: 10.1016/J.Asoc.2015.04.021  0.311
2015 Liang D, Pedrycz W, Liu D, Hu P. Three-way decisions based on decision-theoretic rough sets under linguistic assessment with the aid of group decision making Applied Soft Computing Journal. 29: 256-269. DOI: 10.1016/J.Asoc.2015.01.008  0.348
2015 Liu X, Wang X, Pedrycz W. Fuzzy clustering with semantic interpretation Applied Soft Computing Journal. 26: 21-30. DOI: 10.1016/J.Asoc.2014.09.037  0.427
2015 Qin J, Liu X, Pedrycz W. Hesitant Fuzzy Maclaurin Symmetric Mean Operators and Its Application to Multiple-Attribute Decision Making International Journal of Fuzzy Systems. 17: 509-520. DOI: 10.1007/S40815-015-0049-9  0.437
2015 Song M, Shang W, Wang L, Pedrycz W. Analysis of spatiotemporal data relationship using information granules International Journal of Machine Learning and Cybernetics. 8: 1439-1446. DOI: 10.1007/S13042-015-0386-X  0.618
2015 He ZM, Chan PPK, Yeung DS, Pedrycz W, Ng WWY. Quantification of side-channel information leaks based on data complexity measures for web browsing International Journal of Machine Learning and Cybernetics. 6: 607-619. DOI: 10.1007/S13042-015-0348-3  0.33
2015 Pedrycz W, Al-Hmouz R, Balamash AS, Morfeq A. Modeling with linguistic entities and linguistic descriptors: a perspective of granular computing Soft Computing. DOI: 10.1007/s00500-015-1884-1  0.399
2015 Pedrycz W, Li K, Reformat M. Evolutionary reduction of fuzzy rule-based models Studies in Fuzziness and Soft Computing. 326: 459-481. DOI: 10.1007/978-3-319-19683-1_23  0.38
2015 Prokopowicz P, Pedrycz W. The directed compatibility between ordered fuzzy numbers-A base tool for a direction sensitive fuzzy information processing Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science). 9119: 249-259. DOI: 10.1007/978-3-319-19324-3_23  0.366
2015 Homenda W, Jastrzębska A, Pedrycz W. Nodes selection criteria for fuzzy cognitive maps designed to model time series Advances in Intelligent Systems and Computing. 323: 859-870. DOI: 10.1007/978-3-319-11310-4_75  0.385
2015 Pedrycz W. Fuzzy sets of higher type and higher order in fuzzy modeling Frontiers of Higher Order Fuzzy Sets. 31-49. DOI: 10.1007/978-1-4614-3442-9_3  0.379
2015 Lu W, Zhang L, Liu X, Yang J, Pedrycz W. A human-computer cooperation fuzzy c-means clustering with interval-valued weights International Journal of Intelligent Systems. 30: 81-98. DOI: 10.1002/Int.21683  0.402
2015 Feng F, Pedrycz W. On scalar products and decomposition theorems of fuzzy soft sets Journal of Multiple-Valued Logic and Soft Computing. 25: 45-80.  0.358
2014 Huang W, Oh SK, Pedrycz W. Design of hybrid radial basis function neural networks (HRBFNNs) realized with the aid of hybridization of fuzzy clustering method (FCM) and polynomial neural networks (PNNs). Neural Networks : the Official Journal of the International Neural Network Society. 60: 166-81. PMID 25233483 DOI: 10.1016/J.Neunet.2014.08.007  0.477
2014 Wang S, Watada J, Pedrycz W. Granular robust mean-CVaR feedstock flow planning for waste-to-energy systems under integrated uncertainty. Ieee Transactions On Cybernetics. 44: 1846-57. PMID 25222726 DOI: 10.1109/Tcyb.2013.2296500  0.386
2014 Xu X, Huang Z, Graves D, Pedrycz W. A clustering-based graph Laplacian framework for value function approximation in reinforcement learning. Ieee Transactions On Cybernetics. 44: 2613-25. PMID 24802018 DOI: 10.1109/Tcyb.2014.2311578  0.37
2014 Wu G, Pedrycz W, Ma M, Qiu D, Li H, Liu J. A particle swarm optimization variant with an inner variable learning strategy. Thescientificworldjournal. 2014: 713490. PMID 24587746 DOI: 10.1155/2014/713490  0.341
2014 Zhang H, Pedrycz W, Miao D, Wei Z. From principal curves to granular principal curves. Ieee Transactions On Cybernetics. 44: 748-60. PMID 23996588 DOI: 10.1109/Tcyb.2013.2270294  0.484
2014 Izakian H, Pedrycz W. Anomaly Detection and Characterization in Spatial Time Series Data: A Cluster-Centric Approach Ieee Transactions On Fuzzy Systems. 22: 1612-1624. DOI: 10.1109/Tfuzz.2014.2302456  0.404
2014 Pedrycz W, Izakian H. Cluster-Centric Fuzzy Modeling Ieee Transactions On Fuzzy Systems. 22: 1585-1597. DOI: 10.1109/Tfuzz.2014.2300134  0.503
2014 Pedrycz W, Homenda W. From fuzzy cognitive maps to granular cognitive maps Ieee Transactions On Fuzzy Systems. 22: 859-869. DOI: 10.1109/Tfuzz.2013.2277730  0.425
2014 Chen J, Pedrycz W, Ma L, Wang C. A new information security risk analysis method based on membership degree Kybernetes. 43: 686-698. DOI: 10.1108/K-10-2013-0235  0.36
2014 Izakian H, Pedrycz W. Agreement-based fuzzy C-means for clustering data with blocks of features Neurocomputing. 127: 266-280. DOI: 10.1016/J.Neucom.2013.08.006  0.449
2014 Lu W, Yang J, Liu X, Pedrycz W. The modeling and prediction of time series based on synergy of high-order fuzzy cognitive map and fuzzy c-means clustering Knowledge-Based Systems. 70: 242-255. DOI: 10.1016/J.Knosys.2014.07.004  0.449
2014 Pedrycz W, Al-Hmouz R, Morfeq A, Balamash AS. Building granular fuzzy decision support systems Knowledge-Based Systems. 58: 3-10. DOI: 10.1016/J.Knosys.2013.07.022  0.436
2014 Park J, Jeon M, Pedrycz W. Spectral clustering with physical intuition on spring–mass dynamics Journal of the Franklin Institute. 351: 3245-3268. DOI: 10.1016/J.Jfranklin.2014.02.017  0.325
2014 Cimino MGCA, Lazzerini B, Marcelloni F, Pedrycz W. Genetic interval neural networks for granular data regression Information Sciences. 257: 313-330. DOI: 10.1016/J.Ins.2012.12.049  0.426
2014 Herrera-Viedma E, Cabrerizo FJ, Kacprzyk J, Pedrycz W. A review of soft consensus models in a fuzzy environment Information Fusion. 17: 4-13. DOI: 10.1016/J.Inffus.2013.04.002  0.379
2014 Pedrycz W, Song M. A granulation of linguistic information in AHP decision-making problems Information Fusion. 17: 93-101. DOI: 10.1016/J.Inffus.2011.09.003  0.589
2014 Acampora G, Pedrycz W, Vasilakos AV. Efficient modeling of MIMO systems through Timed Automata based Neuro-Fuzzy Inference Engine International Journal of Approximate Reasoning. 55: 1336-1356. DOI: 10.1016/J.Ijar.2014.02.003  0.447
2014 Nguyen CH, Huynh VN, Pedrycz W. A construction of sound semantic linguistic scales using 4-tuple representation of term semantics International Journal of Approximate Reasoning. 55: 763-786. DOI: 10.1016/J.Ijar.2013.10.012  0.35
2014 Kerr-Wilson J, Pedrycz W. Some new qualitative insights into quality of fuzzy rule-based models Fuzzy Sets and Systems. DOI: 10.1016/J.Fss.2016.05.002  0.441
2014 Hu X, Pedrycz W, Castillo O, Melin P. Fuzzy rule-based models with interactive rules and their granular generalization Fuzzy Sets and Systems. DOI: 10.1016/J.Fss.2016.03.005  0.477
2014 Oh SK, Yoo SH, Pedrycz W. A comparative study of feature extraction methods and their application to P-RBF NNs in face recognition problem Fuzzy Sets and Systems. DOI: 10.1016/J.Fss.2015.11.018  0.369
2014 Pedrycz W. From fuzzy data analysis and fuzzy regression to granular fuzzy data analysis Fuzzy Sets and Systems. DOI: 10.1016/J.Fss.2014.04.017  0.457
2014 Cabrerizo FJ, Ureña R, Pedrycz W, Herrera-Viedma E. Building consensus in group decision making with an allocation of information granularity Fuzzy Sets and Systems. 255: 115-127. DOI: 10.1016/J.Fss.2014.03.016  0.407
2014 Oh SK, Kim WD, Pedrycz W, Seo K. Fuzzy Radial Basis Function Neural Networks with information granulation and its parallel genetic optimization Fuzzy Sets and Systems. 237: 96-117. DOI: 10.1016/J.Fss.2013.08.011  0.519
2014 Isazadeh A, Pedrycz W, Mahan F. ECA rule learning in dynamic environments Expert Systems With Applications. 41: 7847-7857. DOI: 10.1016/J.Eswa.2014.06.028  0.392
2014 Roh SB, Pedrycz W, Ahn TC. A design of granular fuzzy classifier Expert Systems With Applications. 41: 6786-6795. DOI: 10.1016/J.Eswa.2014.04.040  0.437
2014 Zhang L, Pedrycz W, Lu W, Liu X. An interval weighed fuzzy c-means clustering by genetically guided alternating optimization Expert Systems With Applications. 41: 5960-5971. DOI: 10.1016/J.Eswa.2014.03.042  0.394
2014 Lu W, Pedrycz W, Liu X, Yang J, Li P. The modeling of time series based on fuzzy information granules Expert Systems With Applications. 41: 3799-3808. DOI: 10.1016/J.Eswa.2013.12.005  0.462
2014 Wang L, Liu X, Pedrycz W, Shao Y. Determination of temporal information granules to improve forecasting in fuzzy time series Expert Systems With Applications. 41: 3134-3142. DOI: 10.1016/J.Eswa.2013.10.046  0.405
2014 Yu Y, Pedrycz W, Miao D. Multi-label classification by exploiting label correlations Expert Systems With Applications. 41: 2989-3004. DOI: 10.1016/J.Eswa.2013.10.030  0.319
2014 Pedrycz W. Allocation of information granularity in optimization and decision-making models: Towards building the foundations of Granular Computing European Journal of Operational Research. 232: 137-145. DOI: 10.1016/J.Ejor.2012.03.038  0.423
2014 Zaniewski K, Pedrycz W. A hybrid optimization approach to conformance testing of finite automata Applied Soft Computing Journal. 23: 91-103. DOI: 10.1016/J.Asoc.2014.05.018  0.336
2014 Wang X, Pedrycz W, Niu R. Spatio-temporal analysis of Quaternary deposit landslides in the Three Gorges Natural Hazards. 75: 2793-2813. DOI: 10.1007/S11069-014-1462-3  0.304
2014 Russo B, Succi G, Pedrycz W. Mining system logs to learn error predictors: a case study of a telemetry system Empirical Software Engineering. 20: 879-927. DOI: 10.1007/S10664-014-9303-2  0.308
2014 Rajati MR, Khaloozadeh H, Pedrycz W. Fuzzy logic and self-referential reasoning: A comparative study with some new concepts Artificial Intelligence Review. 41: 331-357. DOI: 10.1007/S10462-011-9311-1  0.419
2014 Homenda W, Pedrycz W. Automatic data understanding a linguistic tool for granular cognitive maps designing Advances in Intelligent Systems and Computing. 322: 217-228. DOI: 10.1007/978-3-319-11313-5_21  0.334
2014 Aliev R, Pedrycz W, Zeinalova LM, Huseynov OH. Decision making with second-order imprecise probabilities International Journal of Intelligent Systems. 29: 137-160. DOI: 10.1002/Int.21630  0.364
2013 Song M, Pedrycz W. Granular neural networks: concepts and development schemes. Ieee Transactions On Neural Networks and Learning Systems. 24: 542-53. PMID 24808376 DOI: 10.1109/Tnnls.2013.2237787  0.632
2013 Pedrycz W, Al-Hmouz R, Morfeq A, Balamash A. The design of free structure granular mappings: the use of the principle of justifiable granularity. Ieee Transactions On Cybernetics. 43: 2105-13. PMID 23757519 DOI: 10.1109/Tcyb.2013.2240384  0.443
2013 Pedrycz W. Associations Among Information Granules and Their Optimization in Granulation-Degranulation Mechanism of Granular Computing International Journal of Fuzzy Logic and Intelligent Systems. 13: 245-253. DOI: 10.5391/Ijfis.2013.13.4.245  0.378
2013 Pedrycz W. From Numeric to Granular Description and Interpretation of Information Granules Fundamenta Informaticae. 127: 399-412. DOI: 10.3233/Fi-2013-917  0.477
2013 ALIEV RA, PEDRYCZ W, HUSEYNOV OH. BEHAVIORAL DECISION MAKING WITH COMBINED STATES UNDER IMPERFECT INFORMATION International Journal of Information Technology & Decision Making. 12: 619-645. DOI: 10.1142/S0219622013500235  0.362
2013 PEDRYCZ W. KNOWLEDGE MANAGEMENT AND SEMANTIC MODELING: A ROLE OF INFORMATION GRANULARITY International Journal of Software Engineering and Knowledge Engineering. 23: 5-11. DOI: 10.1142/S0218194013400019  0.321
2013 Tahayori H, Sadeghian A, Pedrycz W. Induction of Shadowed Sets Based on the Gradual Grade of Fuzziness Ieee Transactions On Fuzzy Systems. 21: 937-949. DOI: 10.1109/Tfuzz.2012.2236843  0.467
2013 Pedrycz W. Proximity-Based Clustering: A Search for Structural Consistency in Data With Semantic Blocks of Features Ieee Transactions On Fuzzy Systems. 21: 978-982. DOI: 10.1109/Tfuzz.2012.2236842  0.347
2013 Izakian H, Pedrycz W, Jamal I. Clustering Spatiotemporal Data: An Augmented Fuzzy C-Means Ieee Transactions On Fuzzy Systems. 21: 855-868. DOI: 10.1109/Tfuzz.2012.2233479  0.387
2013 Kim WD, Oh SK, Seo KS, Pedrycz W. A design of FCM-based interval type-2 fuzzy neural network classifier with the aid of PSO Proceedings of the 2013 Joint Ifsa World Congress and Nafips Annual Meeting, Ifsa/Nafips 2013. 1209-1214. DOI: 10.1109/IFSA-NAFIPS.2013.6608573  0.365
2013 Tsehayae AA, Pedrycz W, Fayek AR. Application of granular fuzzy modeling for abstracting labour productivity knowledge bases Proceedings of the 2013 Joint Ifsa World Congress and Nafips Annual Meeting, Ifsa/Nafips 2013. 1096-1101. DOI: 10.1109/IFSA-NAFIPS.2013.6608553  0.323
2013 Kim WD, Oh SK, Seo KS, Pedrycz W. Growing rule-based fuzzy model developed with the aid of fuzzy clustering Proceedings of the 2013 Joint Ifsa World Congress and Nafips Annual Meeting, Ifsa/Nafips 2013. 573-578. DOI: 10.1109/IFSA-NAFIPS.2013.6608464  0.39
2013 Zhang H, Pedrycz W, Miao D, Zhong C. A global structure-based algorithm for detecting the principal graph from complex data Pattern Recognition. 46: 1638-1647. DOI: 10.1016/J.Patcog.2012.11.015  0.319
2013 Oh S, Kim W, Park B, Pedrycz W. A design of granular-oriented self-organizing hybrid fuzzy polynomial neural networks Neurocomputing. 119: 292-307. DOI: 10.1016/J.Neucom.2013.03.029  0.46
2013 Bereta M, Pedrycz W, Reformat M. Local descriptors and similarity measures for frontal face recognition: A comparative analysis Journal of Visual Communication and Image Representation. 24: 1213-1231. DOI: 10.1016/J.Jvcir.2013.08.004  0.312
2013 Huang W, Oh S, Pedrycz W. A fuzzy time-dependent project scheduling problem Information Sciences. 246: 100-114. DOI: 10.1016/J.Ins.2013.05.026  0.416
2013 Park B, Oh S, Pedrycz W. The design of polynomial function-based neural network predictors for detection of software defects Information Sciences. 229: 40-57. DOI: 10.1016/J.Ins.2011.01.026  0.464
2013 Yu Y, Pedrycz W, Miao D. Neighborhood rough sets based multi-label classification for automatic image annotation International Journal of Approximate Reasoning. 54: 1373-1387. DOI: 10.1016/J.Ijar.2013.06.003  0.371
2013 Liang D, Liu D, Pedrycz W, Hu P. Triangular fuzzy decision-theoretic rough sets International Journal of Approximate Reasoning. 54: 1087-1106. DOI: 10.1016/J.Ijar.2013.03.014  0.419
2013 Nguyen CH, Pedrycz W, Duong TL, Tran TS. A genetic design of linguistic terms for fuzzy rule based classifiers International Journal of Approximate Reasoning. 54: 1-21. DOI: 10.1016/J.Ijar.2012.07.007  0.467
2013 Wang L, Liu X, Pedrycz W. Effective intervals determined by information granules to improve forecasting in fuzzy time series Expert Systems With Applications. 40: 5673-5679. DOI: 10.1016/J.Eswa.2013.04.026  0.446
2013 Bereta M, Pedrycz W, Reformat M. Analysis and design of rank-based classifiers Expert Systems With Applications. 40: 3256-3265. DOI: 10.1016/J.Eswa.2012.12.038  0.324
2013 Oh S, Yoo S, Pedrycz W. Design of face recognition algorithm using PCA -LDA combined for hybrid data pre-processing and polynomial-based RBF neural networks : Design and its application Expert Systems With Applications. 40: 1451-1466. DOI: 10.1016/J.Eswa.2012.08.046  0.474
2013 Cabrerizo FJ, Herrera-Viedma E, Pedrycz W. A method based on PSO and granular computing of linguistic information to solve group decision making problems defined in heterogeneous contexts European Journal of Operational Research. 230: 624-633. DOI: 10.1016/J.Ejor.2013.04.046  0.387
2013 Liu X, Feng X, Pedrycz W. Extraction of fuzzy rules from fuzzy decision trees: An axiomatic fuzzy sets (AFS) approach Data & Knowledge Engineering. 84: 1-25. DOI: 10.1016/j.datak.2012.12.001  0.341
2013 Pedrycz W, Homenda W. Building the fundamentals of granular computing: A principle of justifiable granularity Applied Soft Computing. 13: 4209-4218. DOI: 10.1016/J.Asoc.2013.06.017  0.427
2013 Huang W, Oh S, Guo Z, Pedrycz W. A space search optimization algorithm with accelerated convergence strategies Applied Soft Computing. 13: 4659-4675. DOI: 10.1016/J.Asoc.2013.06.005  0.333
2013 Pedrycz W. Granular Computing as a Framework of System Modeling Journal of Control, Automation and Electrical Systems. 24: 81-86. DOI: 10.1007/S40313-013-0010-9  0.399
2013 Aliev RA, Pedrycz W, Alizadeh AV, Huseynov OH. Fuzzy optimality based decision making under imperfect information without utility Fuzzy Optimization and Decision Making. 12: 357-372. DOI: 10.1007/S10700-013-9160-2  0.434
2013 Park B, Kim W, Oh S, Pedrycz W. Fuzzy set-oriented neural networks based on fuzzy polynomial inference and dynamic genetic optimization Knowledge and Information Systems. 39: 207-240. DOI: 10.1007/S10115-012-0610-X  0.475
2013 Zhai K, Jiang N, Pedrycz W. Cost prediction method based on an improved fuzzy model The International Journal of Advanced Manufacturing Technology. 65: 1045-1053. DOI: 10.1007/S00170-012-4238-5  0.403
2013 Azhar Ramli A, Watada J, Pedrycz W. A combination of genetic algorithm-based fuzzy C-means with a convex hull-based regression for real-time fuzzy switching regression analysis: application to industrial intelligent data analysis Ieej Transactions On Electrical and Electronic Engineering. 9: 71-82. DOI: 10.1002/Tee.21938  0.469
2012 Izakian H, Pedrycz W. A new PSO-optimized geometry of spatial and spatio-temporal scan statistics for disease outbreak detection. Swarm and Evolutionary Computation. 4: 1-11. PMID 32288990 DOI: 10.1016/J.Swevo.2012.02.001  0.324
2012 Zhao J, Liu Q, Wang W, Pedrycz W, Cong L. Hybrid neural prediction and optimized adjustment for coke oven gas system in steel industry. Ieee Transactions On Neural Networks and Learning Systems. 23: 439-50. PMID 24808550 DOI: 10.1109/Tnnls.2011.2179309  0.326
2012 Kim I, Watada J, Pedrycz W, Wu JY. Pattern clustering with statistical methods using a DNA-based algorithm. Ieee Transactions On Nanobioscience. 11: 100-10. PMID 22665391 DOI: 10.1109/Tnb.2012.2190618  0.325
2012 Pedrycz W, Bargiela A. An optimization of allocation of information granularity in the interpretation of data structures: toward granular fuzzy clustering. Ieee Transactions On Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the Ieee Systems, Man, and Cybernetics Society. 42: 582-90. PMID 22067434 DOI: 10.1109/TSMCB.2011.2170067  0.356
2012 Gacek A, Pedrycz W. A characterization of electrocardiogram signals through optimal allocation of information granularity. Artificial Intelligence in Medicine. 54: 125-34. PMID 22000296 DOI: 10.1016/J.Artmed.2011.09.007  0.407
2012 Pedrycz W. Fuzzy neural networks with reference neurons as pattern classifiers. Ieee Transactions On Neural Networks. 3: 770-5. PMID 18276475 DOI: 10.1109/72.159065  0.333
2012 Pedrycz W, Waletzky J. Fuzzy clustering with partial supervision. Ieee Transactions On Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the Ieee Systems, Man, and Cybernetics Society. 27: 787-95. PMID 18263089 DOI: 10.1109/3477.623232  0.355
2012 Pedrycz W, de Oliveira JV. Optimization of fuzzy models. Ieee Transactions On Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the Ieee Systems, Man, and Cybernetics Society. 26: 627-36. PMID 18263061 DOI: 10.1109/3477.517038  0.34
2012 Pedrycz W. Shadowed sets: representing and processing fuzzy sets. Ieee Transactions On Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the Ieee Systems, Man, and Cybernetics Society. 28: 103-9. PMID 18255928 DOI: 10.1109/3477.658584  0.346
2012 Pedrycz W, Waletzky J. Neural-network front ends in unsupervised learning. Ieee Transactions On Neural Networks. 8: 390-401. PMID 18255641 DOI: 10.1109/72.557690  0.369
2012 Pedrycz W, Hirota K, Sessa S. A decomposition of fuzzy relations. Ieee Transactions On Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the Ieee Systems, Man, and Cybernetics Society. 31: 657-63. PMID 18244830 DOI: 10.1109/3477.938269  0.381
2012 Pedrycz W, Vukovich G. Abstraction and specialization of information granules. Ieee Transactions On Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the Ieee Systems, Man, and Cybernetics Society. 31: 106-11. PMID 18244771 DOI: 10.1109/3477.907568  0.352
2012 Bargiela A, Pedrycz W. Recursive information granulation: aggregation and interpretation issues. Ieee Transactions On Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the Ieee Systems, Man, and Cybernetics Society. 33: 96-112. PMID 18238160 DOI: 10.1109/TSMCB.2003.808190  0.301
2012 Ramli AA, Watada J, Pedrycz W. An efficient solution of real-time fuzzy regression analysis to information granules problem Journal of Advanced Computational Intelligence and Intelligent Informatics. 16: 199-209. DOI: 10.20965/Jaciii.2012.P0199  0.392
2012 Pizzi NJ, Pedrycz W. Classifying high-dimensional patterns using a fuzzy logic discriminant network Advances in Fuzzy Systems. DOI: 10.1155/2012/920920  0.389
2012 Ahmad SSS, Pedrycz W. Data and Feature Reduction in Fuzzy Modeling through Particle Swarm Optimization Applied Computational Intelligence and Soft Computing. 2012: 1-21. DOI: 10.1155/2012/347157  0.381
2012 ALIEV RA, PEDRYCZ W, HUSEYNOV OH. DECISION THEORY WITH IMPRECISE PROBABILITIES International Journal of Information Technology & Decision Making. 11: 271-306. DOI: 10.1142/S0219622012400032  0.434
2012 Breve F, Zhao L, Quiles M, Pedrycz W, Liu J. Particle Competition and Cooperation in Networks for Semi-Supervised Learning Ieee Transactions On Knowledge and Data Engineering. 24: 1686-1698. DOI: 10.1109/Tkde.2011.119  0.353
2012 Coletta LFS, Vendramin L, Hruschka ER, Campello RJGB, Pedrycz W. Collaborative Fuzzy Clustering Algorithms: Some Refinements and Design Guidelines Ieee Transactions On Fuzzy Systems. 20: 444-462. DOI: 10.1109/Tfuzz.2011.2175400  0.399
2012 Graves D, Noppen J, Pedrycz W. Clustering with proximity knowledge and relational knowledge Pattern Recognition. 45: 2633-2644. DOI: 10.1016/J.Patcog.2011.12.019  0.366
2012 Oh S, Kim W, Pedrycz W, Joo S. Design of K-means clustering-based polynomial radial basis function neural networks (pRBF NNs) realized with the aid of particle swarm optimization and differential evolution Neurocomputing. 78: 121-132. DOI: 10.1016/J.Neucom.2011.06.031  0.366
2012 Mitra S, Kundu PP, Pedrycz W. Feature selection using structural similarity Information Sciences. 198: 48-61. DOI: 10.1016/J.Ins.2012.02.042  0.385
2012 Aliev R, Pedrycz W, Fazlollahi B, Huseynov O, Alizadeh A, Guirimov B. Fuzzy logic-based generalized decision theory with imperfect information Information Sciences. 189: 18-42. DOI: 10.1016/J.Ins.2011.11.027  0.389
2012 Pedrycz W, Song M. Granular fuzzy models: a study in knowledge management in fuzzy modeling International Journal of Approximate Reasoning. 53: 1061-1079. DOI: 10.1016/J.Ijar.2012.05.002  0.619
2012 Pedrycz A, Hirota K, Pedrycz W, Dong F. Granular representation and granular computing with fuzzy sets Fuzzy Sets and Systems. 203: 17-32. DOI: 10.1016/J.Fss.2012.03.009  0.452
2012 Roh S, Ahn T, Pedrycz W. Fuzzy linear regression based on Polynomial Neural Networks Expert Systems With Applications. 39: 8909-8928. DOI: 10.1016/J.Eswa.2012.02.016  0.478
2012 Pedrycz W, Syed Ahmad SS. Evolutionary feature selection via structure retention Expert Systems With Applications. 39: 11801-11807. DOI: 10.1016/J.Eswa.2011.09.154  0.668
2012 Liu X, Zhai K, Pedrycz W. An improved association rules mining method Expert Systems With Applications. 39: 1362-1374. DOI: 10.1016/J.Eswa.2011.08.018  0.329
2012 Park H, Pedrycz W, Chung Y, Oh S. Modeling of the charging characteristic of linear-type superconducting power supply using granular-based radial basis function neural networks Expert Systems With Applications. 39: 1021-1039. DOI: 10.1016/J.Eswa.2011.07.103  0.375
2012 Oh S, Kim W, Pedrycz W. Design of optimized cascade fuzzy controller based on differential evolution: Simulation studies and practical insights Engineering Applications of Artificial Intelligence. 25: 520-532. DOI: 10.1016/J.Engappai.2012.01.002  0.407
2012 Wang X, Liu X, Pedrycz W, Zhu X, Hu G. Mining axiomatic fuzzy set association rules for classification problems European Journal of Operational Research. 218: 202-210. DOI: 10.1016/J.Ejor.2011.04.022  0.461
2012 Pedrycz W, Song M. A genetic reduction of feature space in the design of fuzzy models Applied Soft Computing. 12: 2801-2816. DOI: 10.1016/J.Asoc.2012.03.055  0.65
2012 Pedrycz W, Russo B, Succi G. Knowledge transfer in system modeling and its realization through an optimal allocation of information granularity Applied Soft Computing Journal. 12: 1985-1995. DOI: 10.1016/J.Asoc.2012.02.004  0.409
2012 Lee H, Kim E, Pedrycz W. A new selective neural network ensemble with negative correlation Applied Intelligence. 37: 488-498. DOI: 10.1007/S10489-012-0342-3  0.336
2012 Oh S, Park H, Kim W, Pedrycz W. A new approach to radial basis function-based polynomial neural networks: analysis and design Knowledge and Information Systems. 36: 121-151. DOI: 10.1007/S10115-012-0551-4  0.454
2011 Długosz R, Kolasa M, Pedrycz W, Szulc M. Parallel programmable asynchronous neighborhood mechanism for Kohonen SOM implemented in CMOS technology. Ieee Transactions On Neural Networks / a Publication of the Ieee Neural Networks Council. 22: 2091-104. PMID 22049367 DOI: 10.1109/Tnn.2011.2169809  0.306
2011 Kim I, Chu YY, Watada J, Wu JY, Pedrycz W. A DNA-based algorithm for minimizing decision rules: a rough sets approach. Ieee Transactions On Nanobioscience. 10: 139-51. PMID 22020105 DOI: 10.1109/Tnb.2011.2168535  0.406
2011 Ramli AA, Watada J, Pedrycz W. An intelligent data analysis-base: evaluation of nuclear power plants output flow International Journal of Machine Learning and Computing. 176-184. DOI: 10.7763/Ijmlc.2011.V1.26  0.425
2011 Pedrycz W. Human Centricity and Perception-Based Perspective and Their Centrality to the Agenda of Granular Computing International Journal of Cognitive Informatics and Natural Intelligence. 5: 44-60. DOI: 10.4018/Jcini.2011100104  0.391
2011 Pedrycz W. The Principle of Justifiable Granularity and an Optimization of Information Granularity Allocation as Fundamentals of Granular Computing Journal of Information Processing Systems. 7: 397-412. DOI: 10.3745/Jips.2011.7.3.397  0.426
2011 Minghu H, Chao W, Pedrycz W. The theoretical foundations of statistical learning theory based on fuzzy random samples in Sugeno measure space Transactions of the Institute of Measurement and Control. 34: 520-526. DOI: 10.1177/0142331211403796  0.372
2011 Hu Q, Yu D, Pedrycz W, Chen D. Kernelized Fuzzy Rough Sets and Their Applications Ieee Transactions On Knowledge and Data Engineering. 23: 1649-1667. DOI: 10.1109/Tkde.2010.260  0.498
2011 Pedrycz W, Song M. Analytic Hierarchy Process (AHP) in Group Decision Making and its Optimization With an Allocation of Information Granularity Ieee Transactions On Fuzzy Systems. 19: 527-539. DOI: 10.1109/Tfuzz.2011.2116029  0.593
2011 Mashinchi MH, Orgun MA, Mashinchi M, Pedrycz W. A Tabu–Harmony Search-Based Approach to Fuzzy Linear Regression Ieee Transactions On Fuzzy Systems. 19: 432-448. DOI: 10.1109/Tfuzz.2011.2106791  0.455
2011 Ha M, Chen J, Pedrycz W, Sun L. Bounds on the rate of convergence of learning processes based on random sets and set‐valued probability Kybernetes. 40: 1459-1485. DOI: 10.1108/03684921111169486  0.34
2011 Oh S, Jang H, Pedrycz W. Optimized fuzzy PD cascade controller: A comparative analysis and design Simulation Modelling Practice and Theory. 19: 181-195. DOI: 10.1016/J.Simpat.2010.06.004  0.333
2011 Pedrycz W. Information granules and their use in schemes of knowledge management Scientia Iranica. 18: 602-610. DOI: 10.1016/J.Scient.2011.04.013  0.34
2011 Qian Y, Liang J, Pedrycz W, Dang C. An efficient accelerator for attribute reduction from incomplete data in rough set framework Pattern Recognition. 44: 1658-1670. DOI: 10.1016/J.Patcog.2011.02.020  0.373
2011 Zhou J, Pedrycz W, Miao D. Shadowed sets in the characterization of rough-fuzzy clustering Pattern Recognition. 44: 1738-1749. DOI: 10.1016/J.Patcog.2011.01.014  0.425
2011 Song M, Pedrycz W. From local neural networks to granular neural networks: A study in information granulation Neurocomputing. 74: 3931-3940. DOI: 10.1016/J.Neucom.2011.08.009  0.568
2011 Oh SK, Pedrycz W, Roh SB. Genetically optimized Hybrid Fuzzy Set-based Polynomial Neural Networks Journal of the Franklin Institute. 348: 415-425. DOI: 10.1016/J.Jfranklin.2010.11.005  0.447
2011 Aliev RA, Pedrycz W, Guirimov BG, Aliev RR, Ilhan U, Babagil M, Mammadli S. Type-2 fuzzy neural networks with fuzzy clustering and differential evolution optimization Information Sciences. 181: 1591-1608. DOI: 10.1016/J.Ins.2010.12.014  0.51
2011 Roh SB, Oh SK, Pedrycz W. Design of fuzzy radial basis function-based polynomial neural networks Fuzzy Sets and Systems. 185: 15-37. DOI: 10.1016/J.Fss.2011.06.014  0.483
2011 Bandyopadhyay S, Saha S, Pedrycz W. Use of a fuzzy granulation–degranulation criterion for assessing cluster validity Fuzzy Sets and Systems. 170: 22-42. DOI: 10.1016/J.Fss.2010.11.015  0.401
2011 Oh S, Kim W, Pedrycz W, Park B. Polynomial-based radial basis function neural networks (P-RBF NNs) realized with the aid of particle swarm optimization Fuzzy Sets and Systems. 163: 54-77. DOI: 10.1016/J.Fss.2010.08.007  0.468
2011 Oh S, Jang H, Pedrycz W. A comparative experimental study of type-1/type-2 fuzzy cascade controller based on genetic algorithms and particle swarm optimization Expert Systems With Applications. 38: 11217-11229. DOI: 10.1016/J.Eswa.2011.02.169  0.376
2011 Hu Q, Zhang L, Zhang D, Pan W, An S, Pedrycz W. Measuring relevance between discrete and continuous features based on neighborhood mutual information Expert Systems With Applications. 38: 10737-10750. DOI: 10.1016/J.Eswa.2011.01.023  0.372
2011 Park H, Chung Y, Oh S, Pedrycz W, Kim H. Design of information granule-oriented RBF neural networks and its application to power supply for high-field magnet Engineering Applications of Artificial Intelligence. 24: 543-554. DOI: 10.1016/J.Engappai.2010.11.001  0.411
2011 Ramli AA, Watada J, Pedrycz W. Real-time fuzzy regression analysis: A convex hull approach European Journal of Operational Research. 210: 606-617. DOI: 10.1016/J.Ejor.2010.10.007  0.461
2011 Castillo O, Melin P, Pedrycz W. Design of interval type-2 fuzzy models through optimal granularity allocation Applied Soft Computing. 11: 5590-5601. DOI: 10.1016/J.Asoc.2011.04.005  0.482
2011 Han S, Park S, Pedrycz W. Conditional fuzzy clustering for blind channel equalization Applied Soft Computing. 11: 2777-2786. DOI: 10.1016/J.Asoc.2010.11.008  0.31
2011 Mashinchi MH, Orgun MA, Pedrycz W. Hybrid optimization with improved tabu search Applied Soft Computing. 11: 1993-2006. DOI: 10.1016/J.Asoc.2010.06.015  0.324
2011 Pedrycz W, Chen SC, Rubin SH, Lee G. Risk evaluation through decision-support architectures in threat assessment and countering terrorism Applied Soft Computing Journal. 11: 621-631. DOI: 10.1016/J.Asoc.2009.12.022  0.436
2010 Dlugosz R, Talaska T, Pedrycz W, Wojtyna R. Realization of the conscience mechanism in CMOS implementation of winner-takes-all self-organizing neural networks. Ieee Transactions On Neural Networks / a Publication of the Ieee Neural Networks Council. 21: 961-71. PMID 20421180 DOI: 10.1109/Tnn.2010.2046497  0.315
2010 Chen L, Chen CL, Pedrycz W. A gradient-descent-based approach for transparent linguistic interface generation in fuzzy models. Ieee Transactions On Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the Ieee Systems, Man, and Cybernetics Society. 40: 1219-30. PMID 19963699 DOI: 10.1109/TSMCB.2009.2036443  0.316
2010 Wang S, Watada J, Pedrycz W. Recourse-based facility-location problems in hybrid uncertain environment. Ieee Transactions On Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the Ieee Systems, Man, and Cybernetics Society. 40: 1176-87. PMID 19955039 DOI: 10.1109/TSMCB.2009.2035630  0.323
2010 Pedrycz W. Conditional fuzzy clustering in the design of radial basis function neural networks. Ieee Transactions On Neural Networks. 9: 601-12. PMID 18252484 DOI: 10.1109/72.701174  0.385
2010 Pedrycz W. Granular Computing and Human-Centricity in Computational Intelligence International Journal of Software Science and Computational Intelligence. 2: 16-31. DOI: 10.4018/Jssci.2010100102  0.464
2010 Sadeghi N, Fayek AR, Pedrycz W. Fuzzy Monte Carlo simulation and risk assessment in construction Computer-Aided Civil and Infrastructure Engineering. 25: 238-252. DOI: 10.1111/J.1467-8667.2009.00632.X  0.391
2010 Roh S, Ahn T, Pedrycz W. The refinement of models with the aid of the fuzzy k-nearest neighbors approach Ieee Transactions On Instrumentation and Measurement. 59: 604-615. DOI: 10.1109/Tim.2009.2025070  0.395
2010 Pedrycz W, Loia V, Senatore S. Fuzzy Clustering With Viewpoints Ieee Transactions On Fuzzy Systems. 18: 274-284. DOI: 10.1109/Tfuzz.2010.2040479  0.462
2010 Pizzi NJ, Demko A, Pedrycz W. Classification using an adaptive fuzzy network Annual Conference of the North American Fuzzy Information Processing Society - Nafips. DOI: 10.1109/NAFIPS.2010.5548179  0.329
2010 Pedrycz W. The development of granular metastructures and their use in a multifaceted representation of data and models Kybernetes. 39: 1184-1200. DOI: 10.1108/03684921011062773  0.45
2010 Pedrycz W. Hierarchical Architectures of Fuzzy Models: From Type-1 fuzzy sets to Information Granules of Higher Type International Journal of Computational Intelligence Systems. 3: 202-214. DOI: 10.1080/18756891.2010.9727691  0.487
2010 Cheng S, Dong R, Pedrycz W. A framework of fuzzy hybrid systems for modelling and control International Journal of General Systems. 39: 165-176. DOI: 10.1080/03081070903427358  0.444
2010 Pedrycz W, Bargiela A. Fuzzy clustering with semantically distinct families of variables: Descriptive and predictive aspects Pattern Recognition Letters. 31: 1952-1958. DOI: 10.1016/J.Patrec.2010.06.018  0.376
2010 Mitra S, Pedrycz W, Barman B. Shadowed c-means: Integrating fuzzy and rough clustering Pattern Recognition. 43: 1282-1291. DOI: 10.1016/J.Patcog.2009.09.029  0.388
2010 Roh S, Joo S, Pedrycz W, Oh S. The development of fuzzy radial basis function neural networks based on the concept of information ambiguity Neurocomputing. 73: 2464-2477. DOI: 10.1016/J.Neucom.2010.05.006  0.495
2010 Roh S, Oh S, Pedrycz W. A fuzzy ensemble of parallel polynomial neural networks with information granules formed by fuzzy clustering Knowledge-Based Systems. 23: 202-219. DOI: 10.1016/J.Knosys.2009.12.002  0.476
2010 Pizzi NJ, Pedrycz W. Aggregating multiple classification results using fuzzy integration and stochastic feature selection International Journal of Approximate Reasoning. 51: 883-894. DOI: 10.1016/J.Ijar.2010.05.003  0.362
2010 Hu Q, Zhang L, Chen D, Pedrycz W, Yu D. Gaussian kernel based fuzzy rough sets: Model, uncertainty measures and applications International Journal of Approximate Reasoning. 51: 453-471. DOI: 10.1016/J.Ijar.2010.01.004  0.521
2010 Stach W, Kurgan L, Pedrycz W. A divide and conquer method for learning large Fuzzy Cognitive Maps Fuzzy Sets and Systems. 161: 2515-2532. DOI: 10.1016/J.Fss.2010.04.008  0.428
2010 Castillo O, Melin P, Pedrycz W, Kacpzryk J. Preface to the special section on new trends on pattern recognition with fuzzy models Fuzzy Sets and Systems. 161: 1-2. DOI: 10.1016/J.Fss.2009.10.023  0.384
2010 Graves D, Pedrycz W. Kernel-based fuzzy clustering and fuzzy clustering: A comparative experimental study Fuzzy Sets and Systems. 161: 522-543. DOI: 10.1016/J.Fss.2009.10.021  0.435
2010 Roh S, Ahn T, Pedrycz W. The design methodology of radial basis function neural networks based on fuzzy K-nearest neighbors approach Fuzzy Sets and Systems. 161: 1803-1822. DOI: 10.1016/J.Fss.2009.10.014  0.461
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