Batch gradient neuro-fuzzy learning method with smoothing L0 regularization for the first-order Takagi-Sugeno system

Author:

Ma Qingqing1,Qi Chunmei1,Zhang Huisheng1

Affiliation:

1. College of science, Dalian Maritime University, China

Publisher

ACM

Reference21 articles.

1. A. Riid and E. Rustern , " Interpretability of fuzzy systems and its application to process control," 2007 IEEE International Fuzzy Systems Conference,2007 , pp. 1 - 6 . A. Riid and E. Rustern, "Interpretability of fuzzy systems and its application to process control," 2007 IEEE International Fuzzy Systems Conference,2007, pp. 1-6.

2. Interpretability and learning in neuro-fuzzy systems

3. Multiobjective Evolution of Fuzzy Rough Neural Network via Distributed Parallelism for Stock Prediction

4. Adaptive fuzzy-neural-network based on RBFNN control for active power filter;Fei J.;International Journal of Machine Learning and Cybernetics,2018

5. J. Tang , F. Liu , W. Zhang , R. Ke and Y. Zou , " Lane-changes prediction based on adaptive fuzzy neural network," Expert Systems with Application , 2018 . J. Tang, F. Liu, W. Zhang, R. Ke and Y. Zou, "Lane-changes prediction based on adaptive fuzzy neural network," Expert Systems with Application, 2018.

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