Soft sensor for cobalt oxalate synthesis process in cobalt hydrometallurgy based on hybrid model. - Shuning Zhang; Fuli Wang; Dakuo He; Fei Chu (Neural Comput. Appl., 2013)

A hybrid artificial neural network - mechanistic model for centrifugal compressor. - Fei Chu; Fuli Wang; Xiaogang Wang 006; Shuning Zhang (Neural Comput. Appl., 2014)

Adaptive Fuzzy Output-Feedback Tracking Control for a Class of Switched Stochastic Nonlinear Time-Delay Systems. - Yanli Liu 004; Ben Niu 003; Fei Chu; Yanyan Liu (Circuits Syst. Signal Process., 2016)

Software platform for optimal setting control of complex industrial processes. - Wei Dai 004; Fei Chu; Chunyu Yang 001; Ying Chen; Tianyou Chai (ACC, 2017)

Rapid Modeling Method for Performance Prediction of Centrifugal Compressor Based on Model Migration and SVM. - Fei Chu; Bangwu Dai; Wei Dai 004; Runda Jia; Xiaoping Ma; Fuli Wang (IEEE Access, 2017)

Robust Regularized Random Vector Functional Link Network and Its Industrial Application. - Wei Dai 004; Qixin Chen; Fei Chu; Xiaoping Ma; Tianyou Chai (IEEE Access, 2017)

Configurable Platform for Optimal-Setting Control of Grinding Processes. - Wei Dai 004; Gang Huang; Fei Chu; Tianyou Chai (IEEE Access, 2017)

Soft Sensor Model Development for Cobalt Oxalate Synthesis Process Based on Adaptive Gaussian Mixture Regression. - Shuning Zhang; Fei Chu; Guanlong Deng; Fuli Wang (IEEE Access, 2019)

A Minimum-Cost Modeling Method for Nonlinear Industrial Process Based on Multimodel Migration and Bayesian Model Averaging Method. - Fei Chu; Bangwu Dai; Xiaoping Ma; Fuli Wang; Bin Ye (IEEE Trans Autom. Sci. Eng., 2020)

Weighted Broad Learning System and Its Application in Nonlinear Industrial Process Modeling. - Fei Chu; Tao Liang; C. L. Philip Chen; Xuesong Wang 001; Xiaoping Ma (IEEE Trans. Neural Networks Learn. Syst., 2020)

A process transfer model-based optimal compensation control strategy for batch process using just-in-time learning and trust region method. - Fei Chu; Xiang Cheng; Chuang Peng; Runda Jia; Tao Chen 009; Qinglai Wei (J. Frankl. Inst., 2021)

Graph auto encoder-based operation performance assessment method and its application for complex industrial process. - Lili Hao; Fei Chu; Shuangshuang Liao; Yang Xu; Fuli Wang; Xiaoping Ma (ASCC, 2022)

Operating performance assessment of between-mode transitions for multi-mode plant-wide process. - Xiaoyu Zou; Liang Hu; Fuli Wang; Yuqing Chang; Jie Pan; Fei Chu (ASCC, 2022)

A general data-driven nonlinear robust optimization framework based on statistic limit and principal component analysis. - Shulei Zhang; Runda Jia; Dakuo He; Fei Chu; Zhizhong Mao (Comput. Chem. Eng., 2022)

A Residue Amplifier with 85 dB DC Gain and 15 GHz Closed-Loop Bandwidth for 14-Bit 3GSPS Pipeline ADC. - Cece Huang; Weixin Gai; Yuanfu Zhao; Yafei Ji; Fei Chu; Tieliang Zhang (Circuits Syst. Signal Process., 2022)

Self-supervised global context graph neural network for session-based recommendation. - Fei Chu; Caiyan Jia (PeerJ Comput. Sci., 2022)

Frequency-Domain Energy-Concentrated Synchrosqueezing Transform for Frequency-Varying Signal With Linear Group Delay. - Kun Yu 003; Fei Chu; Xuesong Wang 001; Yuhu Cheng (IEEE Trans. Instrum. Meas., 2022)

A hybrid Aquila Optimizer sine cosine Algorithm for Numerical Optimization. - Fei Chu; Jiayang Wang; Fulin Tian (CACML, 2023)

Multi-strategy Improved Multi-objective Harris Hawk Optimization Algorithm with Elite Opposition-based Learning. - Fulin Tian; Jiayang Wang; Fei Chu; Lin Zhou 015 (CACML, 2023)

Operating performance assessment method for industrial process with slowness principle-based LSTM network. - Fei Chu; Shuangshuang Liao; Lili Hao; Pei Wang; Yan Liu; Fuli Wang (Eng. Appl. Artif. Intell., 2023)

Learning broad learning system with controllable sparsity through L0 regularization. - Fei Chu; Guanghui Wang; Jun Wang; C. L. Philip Chen; Xuesong Wang 001 (Appl. Soft Comput., 2023)

Broad Minimax Probability Learning System and its Application in Regression Modeling. - Fei Chu; Tao Liang; C. L. Philip Chen; Xiaoping Ma; Xuesong Wang 001 (IEEE Trans. Syst. Man Cybern. Syst., 2023)

Efficient and effective ensemble broad learning system based on structural diversity. - Fei Chu; Jianwen Wang; Yiwan Cao; Shuai Li (Appl. Soft Comput., 2024)

RFEM: A framework for essential microRNA identification in mice based on rotation forest and multiple feature fusion. - Shu-Hao Wang; Yan Zhao; Chun-Chun Wang; Fei Chu; Lian-Ying Miao; Li Zhang; Linlin Zhuo; Xing Chen 001 (Comput. Biol. Medicine, 2024)

Operating Performance Assessment of Complex Nonlinear Industrial Process Based on Kernel Locally Linear Embedding PLS. - Fei Chu; Shuangshuang Mo; Lili Hao; Ningyun Lu; Fuli Wang (IEEE Trans Autom. Sci. Eng., 2024)

Compact Broad Learning System Based on Fused Lasso and Smooth Lasso. - Fei Chu; Tao Liang; C. L. Philip Chen; Xuesong Wang 001; Xiaoping Ma (IEEE Trans. Cybern., 2024)

Stochastic configuration networks with robust supervised least squares regression. - Fei Chu; Zihang Sun; Yu Wang; Yong Zhang (Neurocomputing, 2025)

Operating performance assessment of industrial process based on MIC-graph convolutional networks with local slow feature analysis. - Lili Hao; Fei Chu; Tao Chen; Mingxing Jia; Fuli Wang (Neural Networks, 2025)

Process Model-Assisted Optimization Control Method Based on Model Predictive Control and Deep Reinforcement Learning for Coordinated Control System in Coal-Fired Power Unit. - Bangwu Dai; Fuli Wang; Yuqing Chang; Fei Chu; Shengjun Song (IEEE Trans Autom. Sci. Eng., 2025)