On evolutionary designing and learning of flexible neuro-fuzzy structures for nonlinear classification-Reference-Cited by-同舟云学术

On evolutionary designing and learning of flexible neuro-fuzzy structures for nonlinear classification

Published:2009-12 Issue:12 Volume:71 Page:e1659-e1672
ISSN:0362-546X
Container-title:Nonlinear Analysis: Theory, Methods & Applications
language:en
Short-container-title:Nonlinear Analysis: Theory, Methods & Applications

Author:

Cpałka Krzysztof

Publisher

Elsevier BV

Subject

Applied Mathematics,Analysis

Reference47 articles.

1. A method for designing flexible neuro-fuzzy systems;Cpałka,2006

2. K. Cpałka, L. Rutkowski, Flexible Takagi–Sugeno fuzzy systems, in: Proceedings of the International Joint Conference on Neural Networks, Montreal, Canada, 2005, pp. 1764–1769

3. K. Cpałka, L. Rutkowski, A new method for designing and reduction of neuro-fuzzy systems, in: Proceedings of the 2006 IEEE International Conference on Fuzzy Systems, Vancouver, BC, Canada, 2006, pp. 8510–8516

4. Fuzzy and Neuro-Fuzzy Intelligent Systems;Czogała,2000

5. Introduction to Neuro-Fuzzy Systems;Fuller,2000

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