Myong K. Jeong
Affiliations: | The University of Tennessee, Knoxville, TN, United States |
Area:
Industrial Engineering, StatisticsGoogle:
"Myong Jeong"
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Publications
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| Kim S, Jeong MK, Elsayed EA. (2020) A penalized likelihood-based quality monitoring via L2-norm regularization for high-dimensional processes Journal of Quality Technology. 52: 265-280 |
| Turkoz M, Kim S, Son Y, et al. (2020) Generalized support vector data description for anomaly detection Pattern Recognition. 100: 107119 |
| Choi J, Kim B, Han CH, et al. (2020) Methodology for Assessing the Contribution of Knowledge Services during the New Product Development Process to Business Performance Expert Systems With Applications. 113860 |
| Kim B, Jeong Y, Jeong MK. (2020) New multivariate kernel density estimator for uncertain data classification Annals of Operations Research. 1-19 |
| Tosyali A, Kim J, Choi J, et al. (2020) New node anomaly detection algorithm based on nonnegative matrix factorization for directed citation networks Annals of Operations Research. 288: 457-474 |
| Kim S, Kim J, Jeong MK, et al. (2019) Monitoring and control of beta-distributed multistage production processes Quality Technology and Quantitative Management. 16: 1-18 |
| Abdella GM, Kim J, Kim S, et al. (2019) An adaptive thresholding-based process variability monitoring Journal of Quality Technology. 51: 242-256 |
| Turkoz M, Kim S, Jeong Y, et al. (2019) Bayesian framework for fault variable identification Journal of Quality Technology. 51: 375-391 |
| Gazzola G, Jeong MK. (2019) Dependence-Biased Clustering for Variable Selection with Random Forests Pattern Recognition. 96: 106980 |
| Kim J, Jeong MK, Elsayed EA. (2017) Monitoring multistage processes with autocorrelated observations International Journal of Production Research. 55: 2385-2396 |