Implementation of evolutionary fuzzy systems
| Autor: | Russell C. Eberhart, Yaobin Chen, Yuhui Shi |
|---|---|
| Rok vydání: | 1999 |
| Předmět: |
Fuzzy classification
Fuzzy rule business.industry Applied Mathematics Computer Science::Neural and Evolutionary Computation Fuzzy set computer.software_genre Defuzzification ComputingMethodologies_PATTERNRECOGNITION Computational Theory and Mathematics Artificial Intelligence Control and Systems Engineering Fuzzy number Fuzzy set operations ComputingMethodologies_GENERAL Artificial intelligence Data mining business computer Evolutionary programming Membership function Mathematics |
| Zdroj: | IEEE Transactions on Fuzzy Systems. 7:109-119 |
| ISSN: | 1063-6706 |
| DOI: | 10.1109/91.755393 |
| Popis: | Evolutionary fuzzy systems are discussed in which the membership function shapes and types and the fuzzy rule set including the number of rules inside it are evolved using a genetic (evolutionary) algorithm. In addition, the genetic parameters (operators) of the evolutionary algorithm are adapted via a fuzzy system. Benefits of the methodology are illustrated in the process of classifying the iris data set. Possible extensions of the methods are summarized. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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