Title :
Fuzzy system identification for composite operation and fuzzy relation by genetic algorithms
Author :
Ohtani, Shinobu ; Kikuchi, Hiroaki ; Yager, Ronald R. ; Nakanishi, Shohachiro
Author_Institution :
Dept. of Electr. Eng., Tokai Univ., Kanagawa, Japan
Abstract :
Genetic Algorithms (GA) are a useful and convenient tool to find the solution in combinatorial optimal problems, and widely used in the various engineering fields. Here we apply GA to identify both of the composite operations and fuzzy relations under that operation at the same time from the given input-output system data. There exist many composite operations and associated fuzzy relations, which satisfy the same input-output system data. Then, it is supposed that many composite operations and fuzzy relations, which satisfy the original data, are generated when we apply GA to this problems. Tne authors propose a method to identify the fuzzy system from these composite operations and fuzzy relations, generated by GA, by an unweighted pair-group method using arithmetic average (UPGMA) which was developed to make a taxonomic tree of the expression in molecular biology
Keywords :
fuzzy systems; genetic algorithms; identification; inference mechanisms; combinatorial optimal problems; composite operation; fuzzy relation; fuzzy system; genetic algorithms; identification; unweighted pair-group method; Educational institutions; Equations; Fuzzy sets; Fuzzy systems; Genetic algorithms; Genetic engineering; Machine intelligence; Mathematical model; Power system modeling; System identification;
Conference_Titel :
Knowledge-Based Intelligent Electronic Systems, 1997. KES '97. Proceedings., 1997 First International Conference on
Conference_Location :
Adelaide, SA
Print_ISBN :
0-7803-3755-7
DOI :
10.1109/KES.1997.616924