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Genetic algorithm-based learning of fuzzy neural networks. Part 1: feed-forward fuzzy neural networks

✍ Scribed by Rafik A. Aliev; Bijan Fazlollahi; Rustam M. Vahidov

Publisher
Elsevier Science
Year
2001
Tongue
English
Weight
93 KB
Volume
118
Category
Article
ISSN
0165-0114

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✦ Synopsis

In spite of great importance of fuzzy feed-forward and recurrent neural networks (FNN) for solving wide range of real-world problems, today there is no e ective learning algorithm for FNN. In this paper we propose an e ective geneticbased learning mechanism for FNN with fuzzy inputs, fuzzy weights expressed as LR-fuzzy numbers, and fuzzy outputs. The e ectiveness of the proposed method is illustrated through simulation of fuzzy regression for quality evaluation and comparison with the widely used learning method based on -cuts and fuzzy arithmetic. Finally, we demonstrate the use of the proposed learning procedure for calculating fuzzy-valued proΓΏt in an oligopolistic environment.

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