Year |
Citation |
Score |
2023 |
Wang L, Song Z, Zhang Z, Huang C. Editorial: Engineering applications of neurocomputing, volume II. Frontiers in Neurorobotics. 17: 1306042. PMID 37936883 DOI: 10.3389/fnbot.2023.1306042 |
0.345 |
|
2022 |
Wang L, Song Z, Zhang Z, Huang C. Editorial: Engineering Applications of Neurocomputing. Frontiers in Neurorobotics. 16: 839505. PMID 35153710 DOI: 10.3389/fnbot.2022.839505 |
0.349 |
|
2020 |
Liu X, Zhang Z, Song Z. A comparative study of the data-driven day-ahead hourly provincial load forecasting methods: From classical data mining to deep learning Renewable and Sustainable Energy Reviews. 119: 109632. DOI: 10.1016/J.Rser.2019.109632 |
0.511 |
|
2019 |
Zhu J, Shen Y, Song Z, Zhou D, Zhang Z, Kusiak A. Data-driven building load profiling and energy management Sustainable Cities and Society. 49: 101587. DOI: 10.1016/J.Scs.2019.101587 |
0.602 |
|
2018 |
Song Z, Zhang Z, Jiang Y, Zhu J. Wind turbine health state monitoring based on a Bayesian data-driven approach Renewable Energy. 125: 172-181. DOI: 10.1016/J.Renene.2018.02.096 |
0.6 |
|
2017 |
Jiang Y, Long H, Zhang Z, Song Z. Day-Ahead Prediction of Bihourly Solar Radiance With a Markov Switch Approach Ieee Transactions On Sustainable Energy. 8: 1536-1547. DOI: 10.1109/Tste.2017.2694551 |
0.536 |
|
2017 |
Long H, Zhang Z, Song Z, Kusiak A. Formulation and Analysis of Grid and Coordinate Models for Planning Wind Farm Layouts Ieee Access. 5: 1810-1819. DOI: 10.1109/Access.2017.2657638 |
0.693 |
|
2016 |
Zhang Z, Song Z. Mining SCADA Data Offers a New Roadmap of Wind Farm Operations and Management Industrial Engineering & Management. 5. DOI: 10.4172/2169-0316.1000E134 |
0.313 |
|
2016 |
Song Z, Zhang Z, Chen X. The decision model of 3-dimensional wind farm layout design Renewable Energy. 85: 248-258. DOI: 10.1016/J.Renene.2015.06.036 |
0.635 |
|
2015 |
Long H, Wang L, Zhang Z, Song Z, Xu J. Data-Driven Wind Turbine Power Generation Performance Monitoring Ieee Transactions On Industrial Electronics. 62: 6627-6635. DOI: 10.1109/Tie.2015.2447508 |
0.619 |
|
2014 |
Song Z, Jiang Y, Zhang Z. Short-term wind speed forecasting with Markov-switching model Applied Energy. 130: 103-112. DOI: 10.1016/J.Apenergy.2014.05.026 |
0.624 |
|
2013 |
Jiang Y, Song Z, Kusiak A. Very short-term wind speed forecasting with Bayesian structural break model Renewable Energy. 50: 637-647. DOI: 10.1016/J.Renene.2012.07.041 |
0.648 |
|
2013 |
Zhang Z, Kusiak A, Song Z. Scheduling electric power production at a wind farm European Journal of Operational Research. 224: 227-238. DOI: 10.1016/J.Ejor.2012.07.043 |
0.703 |
|
2011 |
Song Z, Geng X, Kusiak A, Xu C. Mining Markov chain transition matrix from wind speed time series data Expert Systems With Applications. 38: 10229-10239. DOI: 10.1016/J.Eswa.2011.02.063 |
0.618 |
|
2010 |
Song Z, Kusiak A. Multiobjective optimization of temporal processes. Ieee Transactions On Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the Ieee Systems, Man, and Cybernetics Society. 40: 845-56. PMID 19900853 DOI: 10.1109/TSMCB.2009.2030667 |
0.509 |
|
2010 |
Kusiak A, Song Z. Design of wind farm layout for maximum wind energy capture Renewable Energy. 35: 685-694. DOI: 10.1016/J.Renene.2009.08.019 |
0.642 |
|
2010 |
Kusiak A, Zheng H, Song Z. Power optimization of wind turbines with data mining and evolutionary computation Renewable Energy. 35: 695-702. DOI: 10.1016/J.Renene.2009.08.018 |
0.656 |
|
2010 |
Kusiak A, Li W, Song Z. Dynamic control of wind turbines Renewable Energy. 35: 456-463. DOI: 10.1016/J.Renene.2009.05.022 |
0.648 |
|
2010 |
Song Z, Kusiak A. Mining Pareto-optimal modules for delayed product differentiation European Journal of Operational Research. 201: 123-128. DOI: 10.1016/J.Ejor.2009.02.013 |
0.52 |
|
2009 |
Song Z, Kusiak A. Optimization of temporal processes: A model predictive control approach Ieee Transactions On Evolutionary Computation. 13: 169-179. DOI: 10.1109/Tevc.2008.920680 |
0.578 |
|
2009 |
Kusiak A, Song Z, Zheng H. Anticipatory Control of Wind Turbines With Data-Driven Predictive Models Ieee Transactions On Energy Conversion. 24: 766-774. DOI: 10.1109/Tec.2009.2025320 |
0.659 |
|
2009 |
Kusiak A, Zheng H, Song Z. Short-Term Prediction of Wind Farm Power: A Data Mining Approach Ieee Transactions On Energy Conversion. 24: 125-136. DOI: 10.1109/Tec.2008.2006552 |
0.652 |
|
2009 |
Song Z, Kusiak A. Optimising product configurations with a data-mining approach International Journal of Production Research. 47: 1733-1751. DOI: 10.1080/00207540701644235 |
0.486 |
|
2009 |
Kusiak A, Song Z. Sensor fault detection in power plants Journal of Energy Engineering. 135: 127-137. DOI: 10.1061/(Asce)0733-9402(2009)135:4(127) |
0.509 |
|
2009 |
Kusiak A, Zheng H, Song Z. On-line monitoring of power curves Renewable Energy. 34: 1487-1493. DOI: 10.1016/J.Renene.2008.10.022 |
0.617 |
|
2009 |
Kusiak A, Zheng H, Song Z. Models for monitoring wind farm power Renewable Energy. 34: 583-590. DOI: 10.1016/J.Renene.2008.05.032 |
0.66 |
|
2009 |
Kusiak A, Zheng H, Song Z. Wind farm power prediction: a data-mining approach Wind Energy. 12: 275-293. DOI: 10.1002/We.295 |
0.61 |
|
2008 |
Kusiak A, Song Z. Clustering-based performance optimization of the boiler-turbine system Ieee Transactions On Energy Conversion. 23: 651-658. DOI: 10.1109/Tec.2007.914183 |
0.588 |
|
2007 |
Kusiak A, Smith MR, Song Z. Planning Product Configurations Based on Sales Data Ieee Transactions On Systems, Man and Cybernetics, Part C (Applications and Reviews). 37: 602-609. DOI: 10.1109/TSMCC.2007.897503 |
0.426 |
|
2007 |
Song Z, Kusiak A. Constraint-based control of boiler efficiency: A data-mining approach Ieee Transactions On Industrial Informatics. 3: 73-83. DOI: 10.1109/Tii.2006.890530 |
0.528 |
|
2006 |
Kusiak A, Song Z. Combustion efficiency optimization and virtual testing: A data-mining approach Ieee Transactions On Industrial Informatics. 2: 176-184. DOI: 10.1109/Tii.2006.873598 |
0.53 |
|
2004 |
Song Z. A numerical simulation of dust storms in China Environmental Modelling and Software. 19: 141-151. DOI: 10.1016/S1364-8152(03)00116-6 |
0.344 |
|
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