ACTA UNIVERSITATIS APULENSIS No 12/2006 FUSION BETWEEN FUZZY SYSTEMS, GENETIC ALGORITHMS AND ARTIFICIAL NEURAL NETWORKS
نویسندگان
چکیده
Fuzzy System (FS) and Artificial Neural Networks (ANN) are complementary methods. But while ANN can learn from data FS cannot. Also, Genetic Algorithms (GA) are complementary to FS. While the FS are easy to understand, the GA are not, although they have the ability to learn, and so on. Many researches have been devoted to its fusion. Our purpose is to give a survey of these questions. 2000 Mathematics Subject Classification: Fuzzy Systems, Genetic Algorithms, Artificial Neural Networks, Artificial Intelligence. 1.Introduction to Fuzzy Systems An Expert System (ES) is a program which contains human expert knowledge. It gives answers to the user queries. For this, we need inference methods. A very useful generalization of the mentioned ES is the Fuzzy Expert System (FES). It consists of an ES which can deal with fuzzy information, that is, with some degree of uncertainty. In the ”real world” the human expert can express his or her knowledge by means of linguistic terms. So, we represent, in a natural way, such knowledge by fuzzy rules and linguistic modifiers (that reflect terms as ”almost”, for instance). Therefore, we need to apply fuzzy inference methods. The form in which we usually store the knowledge is the base rule, generally in the logical form: ”if-then”.
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