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2020 – today
- 2024
[j25]Hang Yi, Zhi-gang Su
, Pei-hong Wang:
Closed-Loop Shaping-Based Active Disturbance Rejection Control With Delay Robustness and Application to Wet Desulfurization Process. IEEE Trans. Ind. Electron. 71(6): 6117-6127 (2024)- 2023
- [j24]Hang Yi, Zhi-gang Su, Pei-hong Wang:
Robust tuning of uncertainty and disturbance estimator-based control for stable processes with time delay. J. Frankl. Inst. 360(4): 2594-2616 (2023) - [j23]Hang Yi, Pei-hong Wang, Gang Zhao:
Fractional order active disturbance rejection control design for non-integer order plus time delay models. Trans. Inst. Meas. Control 45(9): 1619-1633 (2023) - [j22]Chaoyu Gong, Zhi-gang Su, Pei-hong Wang, Qian Wang, Yang You:
A Sparse Reconstructive Evidential K-Nearest Neighbor Classifier for High-Dimensional Data. IEEE Trans. Knowl. Data Eng. 35(6): 5563-5576 (2023) - 2022
- [j21]Chaoyu Gong, Zhi-gang Su, Pei-hong Wang, Yang You:
Distributed evidential clustering toward time series with big data issue. Expert Syst. Appl. 191: 116279 (2022) - [j20]Qian Wang, Chaoyu Gong, Pei-hong Wang:
Clustering based on adaptive local density with evidential assigning strategy. Intell. Data Anal. 26(1): 101-118 (2022) - [c9]Lulu Xu, Qian Wang, Pei-hong Wang, Zhi-gang Su:
Evidential Clustering by Competitive Agglomeration. BELIEF 2022: 33-43 - [c8]Chaoyu Gong, Yongbin Liu, Di Fu, Yong Liu, Pei-hong Wang, Yang You:
Self-reconstructive evidential clustering for high-dimensional data. ICDE 2022: 2099-2112 - [c7]Chaoyu Gong, Yongbin Li, Yong Liu, Pei-hong Wang, Yang You:
Joint Evidential $K$-Nearest Neighbor Classification. ICDE 2022: 2113-2126 - 2021
- [j19]Chaoyu Gong, Zhi-gang Su, Pei-hong Wang, Qian Wang, Yang You:
Evidential instance selection for K-nearest neighbor classification of big data. Int. J. Approx. Reason. 138: 123-144 (2021) - [j18]Chaoyu Gong, Zhi-gang Su, Pei-hong Wang, Qian Wang:
An evidential clustering algorithm by finding belief-peaks and disjoint neighborhoods. Pattern Recognit. 113: 107751 (2021) - 2020
- [j17]Chaoyu Gong, Zhi-gang Su, Pei-hong Wang, Qian Wang:
Cumulative belief peaks evidential K-nearest neighbor clustering. Knowl. Based Syst. 200: 105982 (2020) - [j16]Chaoyu Gong, Pei-hong Wang, Zhi-gang Su:
An interactive nonparametric evidential regression algorithm with instance selection. Soft Comput. 24(5): 3125-3140 (2020)
2010 – 2019
- 2019
- [j15]Xiao-long Chen, Pei-hong Wang, Qian Wang, Yi-hua Dong:
A Two-Stage strategy to handle equality constraints in ABC-based power economic dispatch problems. Soft Comput. 23(15): 6679-6696 (2019) - 2018
- [j14]Xiao-long Chen, Pei-hong Wang, Yong-sheng Hao, Ming Zhao:
Evidential KNN-based condition monitoring and early warning method with applications in power plant. Neurocomputing 315: 18-32 (2018) - [j13]Yang Zhao, Pei-hong Wang, Yi-Guo Li, Meng-yang Li:
Fuzzy weighted c-harmonic regressions clustering algorithm. Soft Comput. 22(14): 4595-4611 (2018) - [c6]Zhi-gang Su, Hongyu Zhou, Pei-hong Wang, Gang Zhao, Ming Zhao:
E2CM: An Evolutionary Version of Evidential C-Means Clustering Algorithm. BELIEF 2018: 234-242 - 2017
- [j12]Yong-sheng Hao, Zhi-gang Su, Pei-hong Wang, Ming Zhao:
Constrained fuzzy evidential multivariate model identified by EM algorithm: a soft sensor to monitoring imprecise and uncertain process parameters. Soft Comput. 21(6): 1619-1642 (2017) - 2015
- [j11]Qian Wang, Zhi-gang Su, Babak Rezaee, Pei-hong Wang:
Constructing T-S fuzzy model from imprecise and uncertain knowledge represented as fuzzy belief functions. Neurocomputing 166: 319-336 (2015) - [c5]Xue-sen Quan, Pei-hong Wang, Yong-sheng Hao, Ming Zhao, Meng-yang Li:
Analysis of Line Loss Based on Matlab and Oracle Database. CBD 2015: 327-331 - 2014
- [j10]Zhi-gang Su, Shu-rong Zheng, Pei-hong Wang:
Likelihood-based multivariate fuzzy model with linear inequality constraints. J. Intell. Fuzzy Syst. 27(5): 2191-2209 (2014) - [j9]Zhi-gang Su, Pei-hong Wang:
Regression analysis of belief functions on interval-valued variables: comparative studies. Soft Comput. 18(1): 51-70 (2014) - [c4]Zhi-gang Su, Babak Rezaee, Pei-hong Wang:
Mixture data-driven Takagi-Sugeno fuzzy model. FSKD 2014: 24-30 - 2013
- [j8]Zhi-gang Su, Pei-hong Wang, Zhao-long Song:
Kernel based nonlinear fuzzy regression model. Eng. Appl. Artif. Intell. 26(2): 724-738 (2013) - [j7]Zhi-gang Su, Yifan Wang, Pei-hong Wang:
Parametric regression analysis of imprecise and uncertain data in the fuzzy belief function framework. Int. J. Approx. Reason. 54(8): 1217-1242 (2013) - 2012
- [j6]Zhi-gang Su, Pei-hong Wang, Jiong Shen, Yi-Guo Li, Yu-fei Zhang, En-jun Hu:
Automatic fuzzy partitioning approach using Variable string length Artificial Bee Colony (VABC) algorithm. Appl. Soft Comput. 12(11): 3421-3441 (2012) - [j5]Zhi-gang Su, Pei-hong Wang, Yu-fei Zhang:
Automatic T-S fuzzy model with application to designing predictive controller. Comput. Sci. Inf. Syst. 9(4): 1577-1601 (2012) - [j4]Zhi-gang Su, Pei-hong Wang:
Minimizing neighborhood evidential decision error for feature evaluation and selection based on evidence theory. Expert Syst. Appl. 39(1): 527-540 (2012) - 2011
- [j3]Zhi-gang Su, Pei-hong Wang, Jiong Shen, Xiang-jun Yu, Zhen-zhong Lv, Lu Lu:
Multi-model strategy based evidential soft sensor model for predicting evaluation of variables with uncertainty. Appl. Soft Comput. 11(2): 2595-2610 (2011) - [j2]Zhi-gang Su, Pei-hong Wang, Xiang-jun Yu, Zhen-zhong Lv:
Maximal confidence intervals of the interval-valued belief structure and applications. Inf. Sci. 181(9): 1700-1721 (2011) - [c3]Yu-fei Zhang, Zhi-gang Su, Pei-hong Wang:
A convenient version of T-S fuzzy model with enhanced performance. FSKD 2011: 1074-1079 - 2010
- [j1]Zhi-gang Su, Pei-hong Wang, Xiang-jun Yu:
Immune genetic algorithm-based adaptive evidential model for estimating unmeasured parameter: Estimating levels of coal powder filling in ball mill. Expert Syst. Appl. 37(7): 5246-5258 (2010)
2000 – 2009
- 2009
- [c2]Zhi-gang Su, Pei-hong Wang:
A Robust Adaptive Version of Evidence-Theoretic k-NN Classification Rule. FSKD (4) 2009: 525-529 - [c1]Zhi-gang Su, Pei-hong Wang, Xiang-jun Yu, Zhen-zhong Lv:
Data and knowledge driven adaptive evidential soft sensor model for monitoring unmeasured parameters. ICONS 2009: 420-426
Coauthor Index
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