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Extreme Fuzzy Broad Learning System: Algorithm, Frequency Principle, and Applications in Classification and Regression Journal article
Duan, Junwei, Yao, Shiyi, Tan, Jiantao, Liu, Yang, Chen, Long, Zhang, Zhen, Chen, C. L.P.. Extreme Fuzzy Broad Learning System: Algorithm, Frequency Principle, and Applications in Classification and Regression[J]. IEEE Transactions on Neural Networks and Learning Systems, 2024.
Authors:  Duan, Junwei;  Yao, Shiyi;  Tan, Jiantao;  Liu, Yang;  Chen, Long; et al.
Favorite | TC[WOS]:2 TC[Scopus]:1  IF:10.2/10.4 | Submit date：2024/05/16
Broad Learning System (Bls)  Classification  Deep Neural Network  Feature Extraction  Frequency Principle  Fuzzy Extreme Learning Machine (Elm)  Learning Systems  Mathematical Models  Neural Networks  Regression  Stacking  Task Analysis  Training  
Fuzzy Adaptive Finite-Time Consensus Control for High-Order Nonlinear Multi-Agent Systems Based on Event-Triggered Journal article
Zhou, Haodong, Sui, Shuai, Tong, Shaocheng. Fuzzy Adaptive Finite-Time Consensus Control for High-Order Nonlinear Multi-Agent Systems Based on Event-Triggered[J]. IEEE Transactions on Fuzzy Systems, 2022.
Authors:  Zhou, Haodong;  Sui, Shuai;  Tong, Shaocheng
Favorite | TC[WOS]:36 TC[Scopus]:39  IF:10.7/9.7 | Submit date：2022/05/17
Artificial Neural Networks  Backstepping  Consensus Control  Consensus Control  Control Design  Convergence  Eventtriggered  Finite-time  Fuzzy Logic  High-order Nonlinear Multi-agent Systems  Nonlinear Dynamical Systems  
Fuzzy Neural Networks (FNNs) Training Algorithm with Dropout via Its Equivalent Fully Connected Fuzzy Inference Systems (F-CONFIS) Conference paper
Wang，Jing, Chen，Philip, Ma，Zhenyuan, Xiao，Zhenghong. Fuzzy Neural Networks (FNNs) Training Algorithm with Dropout via Its Equivalent Fully Connected Fuzzy Inference Systems (F-CONFIS)[C], 2018, 80-84.
Authors:  Wang，Jing;  Chen，Philip;  Ma，Zhenyuan;  Xiao，Zhenghong
Favorite | TC[Scopus]:2 | Submit date：2021/03/09
Adaptive Neural-Fuzzy Inference Systems(ANFIS)  Fuzzy Inference Systems  Fuzzy Neural Networks  Gradient Descent  Neural Networks  
A new fast-F-CONFIS training of fully-connected neuro-fuzzy inference system Conference paper
Jing Wang, Yuan-Yan Tang, Long Chen, C. L. Philip Chen, Chao-Tian Chen. A new fast-F-CONFIS training of fully-connected neuro-fuzzy inference system[C]:IEEE, 2015, 99-104.
Authors:  Jing Wang;  Yuan-Yan Tang;  Long Chen;  C. L. Philip Chen;  Chao-Tian Chen
Favorite | TC[WOS]:0 TC[Scopus]:0 | Submit date：2019/02/11
Conjugate Gradients  Fuzzy Logic  Fuzzy Neural Networks  Gradient Descent  Neural Networks  
Mixed radix systems of fully connected neuro-fuzzy inference systems with special properties Conference paper
Wang J., Chen C.-T., Chen C.L.P., Yu Y.-Q.. Mixed radix systems of fully connected neuro-fuzzy inference systems with special properties[C], 2015, 105-109.
Authors:  Wang J.;  Chen C.-T.;  Chen C.L.P.;  Yu Y.-Q.
Favorite | TC[WOS]:0 TC[Scopus]:0 | Submit date：2019/02/11
Fully Connected Neuro-fuzzy System  Fuzzy Logic  Fuzzy Neural Networks  Gradient Descent  Neural Networks  Neuro-fuzzy System  
A novel random fuzzy neural networks for tackling uncertainties of electric load forecasting Journal article
Lou C.W., Dong M.C.. A novel random fuzzy neural networks for tackling uncertainties of electric load forecasting[J]. International Journal of Electrical Power and Energy Systems, 2015, 73, 34.
Authors:  Lou C.W.;  Dong M.C.
Favorite | TC[WOS]:56 TC[Scopus]:63 | Submit date：2018/10/30
Load Forecasting  Random Fuzzy Neural Networks  Random Fuzzy Variable  Uncertainty  
The bounded capacity of fuzzy neural networks (FNNs) via a new fully connected neural fuzzy inference system (F-CONFIS) with its applications Journal article
Wang J., Wang C.-H., Chen C.L.P.. The bounded capacity of fuzzy neural networks (FNNs) via a new fully connected neural fuzzy inference system (F-CONFIS) with its applications[J]. IEEE Transactions on Fuzzy Systems, 2014, 22(6), 1373-1386.
Authors:  Wang J.;  Wang C.-H.;  Chen C.L.P.
Favorite | TC[WOS]:17 TC[Scopus]:21 | Submit date：2019/02/11
Capacity Of Neural Networks  Fuzzy Neural Networks (Fnns)  Fuzzy System  Iris Data  Neural Networks  
A new learning algorithm for a fully connected neuro-fuzzy inference system Journal article
Chen C.L.P., Wang J., Wang C.-H., Chen L.. A new learning algorithm for a fully connected neuro-fuzzy inference system[J]. IEEE Transactions on Neural Networks and Learning Systems, 2014, 25(10), 1741-1757.
Authors:  Chen C.L.P.;  Wang J.;  Wang C.-H.;  Chen L.
Favorite | TC[WOS]:43 TC[Scopus]:46 | Submit date：2019/02/11
Fully Connected Neuro-fuzzy Inference Systems (F-confis)  Fuzzy Logic  Fuzzy Neural Networks  Gradient Descent  Neural Networks (Nns)  Neuro-fuzzy System  Optimal Learning  
Fuzzy neural network-based adaptive control for a class of uncertain nonlinear stochastic systems Journal article
Chen C.L.P., Liu Y.-J., Wen G.-X.. Fuzzy neural network-based adaptive control for a class of uncertain nonlinear stochastic systems[J]. IEEE Transactions on Cybernetics, 2014, 44(5), 583.
Authors:  Chen C.L.P.;  Liu Y.-J.;  Wen G.-X.
Favorite | TC[WOS]:447 TC[Scopus]:483 | Submit date：2018/10/30
Adaptive Control  Backstepping Design  Fuzzy-neural Networks  Nonlinear Stochastic Systems  
On the conjugate gradients (CG) training algorithm of fuzzy neural networks (FNNs) via its equivalent fully connected neural networks (FFNNs) Conference paper
Wang J., Chen C.L.P., Wang C.-H.. On the conjugate gradients (CG) training algorithm of fuzzy neural networks (FNNs) via its equivalent fully connected neural networks (FFNNs)[C], 2012, 2446-2451.
Authors:  Wang J.;  Chen C.L.P.;  Wang C.-H.
Favorite | TC[WOS]:2 TC[Scopus]:3 | Submit date：2019/02/11
Conjugate Gradients  Fuzzy Logic  Fuzzy Neural Networks  Gradient Descent  Neural Networks