[1]Gang Dang, Dianhui Wang*, Online self-learning fuzzy recurrent stochastic configuration networks for modeling nonstationary dynamics, IEEE Transactions on Fuzzy Systems (Early Access), 2025.
[2]Gang Dang, Dianhui Wang*, Self-organizing recurrent stochastic configuration networks for nonstationary data modelling, IEEE Transactions on Industrial Informatics (Early Access), 2025.
[3]Dianhui Wang*, Gang Dang, Fuzzy recurrent stochastic configuration networks for industrial data analytics, IEEE Transactions on Fuzzy Systems, 33(4), 1178-1191, 2025.
[4]Gang Dang, Dianhui Wang*, An improved fuzzy recurrent stochastic configuration network for modeling nonlinear systems, IEEE Transactions on Fuzzy Systems, 33(4), 1265-1276, 2025.
[5]Dianhui Wang*, Pengxin Tian, Wei Dai, Gang Yu, Predicting particle size of copper ore grinding with stochastic configuration networks, IEEE Transactions on Industrial Informatics, 20(11), 12969-12978, 2024.
[6]Yongxuan Chen, Dianhui Wang*, An improved deep kernel partial least squares and its application to industrial data modeling, IEEE Transactions on Industrial Informatics, 20(5), 7894-7903, 2024.
[7]Kang Li, Junfei Qiao*, Dianhui Wang*, Online self-learning stochastic configuration networks for nonstationary data stream analysis, IEEE Transactions on Industrial Informatics 20 (3), 3222-3231, 2023.
[8]Kang Li, Junfei Qiao, Dianhui Wang*, Fuzzy stochastic configuration networks for nonlinear system modeling, IEEE Transactions on Fuzzy Systems 32 (3), 948-957, 2023.
[9]Changqin Huang, Qionghao Huang, Dianhui Wang*, Stochastic configuration networks based adaptive storage replica management for power big data processing, IEEE Transactions on Industrial Informatics 16 (1), 373-383, 2019.
[10]Ming Li, Dianhui Wang*, 2-D stochastic configuration networks for image data analytics, IEEE Transactions on Cybernetics 51 (1), 359-372, 2019.
[11]Dianhui Wang*, Ming Li, Stochastic configuration networks: Fundamentals and algorithms, IEEE Transactions on Cybernetics 47 (10), 3466-3479, 2017.
[12]Hui Yang, Yating Fu, Dianhui Wang*, Multi-ANFIS model based synchronous tracking control of high-speed electric multiple unit, IEEE Transactions on Fuzzy Systems 26 (3), 1472-1484, 2017.
[13]Sarwar Tapan, Dianhui Wang*, A further study on mining DNA motifs using fuzzy self-organizing maps, IEEE Transactions on Neural Networks and Learning Systems 27 (1), 113-124, 2015.
[14]Weitao Li, Dianhui Wang*, Tianyou Chai, Multisource data ensemble modeling for clinker free lime content estimate in rotary kiln sintering processes, IEEE Transactions on Systems, Man, and Cybernetics: Systems 45 (2), 303-314, 2014.
[15]Dianhui Wang*, Sarwar Tapan，A robust elicitation algorithm for discovering DNA motifs using fuzzy self-organizing maps，IEEE Transactions on Neural Networks and Learning Systems 24 (10), 1677-1688, 2013.
[16]Weitao Li, Dianhui Wang*, Tianyou Chai, Flame image-based burning state recognition for sintering process of rotary kiln using heterogeneous features and fuzzy integral, IEEE Transactions on Industrial Informatics 8 (4), 780-790, 2012.
[17]Yongfu Wang, Dianhui Wang*, Tianyou Chai, Extraction and adaptation of fuzzy rules for friction modeling and control compensation, IEEE Transactions on Fuzzy Systems 19 (4), 682-693, 2011.
[18]Runyi Yu, Dianhui Wang*, On impulsive modes of linear singular systems subject to decentralized output feedback, IEEE Transactions on Automatic Control 48 (10), 1804-1809, 2003.
[19]Runyi Yu, Dianhui Wang*, Algebraic properties of singular systems subject to decentralized output feedback, IEEE Transactions on Automatic Control 47 (11), 1898-1903, 2002.
[20]Dianhui Wang*, Paul Bao, Robust impulse control of uncertain singular systems by decentralized output feedback, IEEE Transactions on Automatic Control 45 (3), 500-505, 2000.
[21]Dianhui Wang*, C. B. Soh, On regularizing singular systems by decentralized output feedback, IEEE Transactions on Automatic Control 44 (1), 148-152, 1999.
