Fuzzy model identification by evolutionary, gradient based and memtic algorithms

Botzheim, J.; Kóczy, László T.; Ruano, Antonio

http://hdl.handle.net/10400.1/2316

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Authors

Botzheim, J.

Kóczy, László T.

Ruano, Antonio

Abstract(s)

One of the crucial problems of fuzzy rule modeling is how to find an optimal or at least a quasi-optimal rule base fro a certain system. In most applications there is no human expert available, or, the result of a human expert's decision is too much subjective and is not reproducible, thus some automatic method to determine the fuzzy rule base must be deployed.

URI

http://hdl.handle.net/10400.1/2316

Citation

Botzheim, J.; Koczy, Laszlo T.; Ruano, A. E. Fuzzy Model Identification by Evolutionary, Gradient Based and Memtic Algorithms, Trabalho apresentado em Gyor Symposium on Computational Intelligence, In Proceedings of the Gyor Symposium on Computational Intelligence, Gyor, 2008.