Title :
Genetic learning and optimization of fuzzy sets in fuzzy rule-based system
Author :
Pires, M.G. ; Camargo, H.A.
Author_Institution :
Dept. of Comput. Sci., Univ. Fed. de Sao Carlos, Brazil
Abstract :
This work presents a comparative study of two genetic approaches to fuzzy systems generation, where the genetic algorithm is applied to the fuzzy sets. In the first approach a previously defined database is tuned considering a fixed rule base, and in the second one the database is generated through the GA with the posteriori definition of the rule base for each newly generated database. Experimental results are presented and discussed.
Keywords :
database management systems; fuzzy set theory; fuzzy systems; genetic algorithms; knowledge based systems; learning (artificial intelligence); database generation; fuzzy rule-based system; fuzzy set optimization; genetic algorithm; genetic learning; Computer science; Design optimization; Fuzzy sets; Fuzzy systems; Genetic algorithms; Humans; Knowledge acquisition; Knowledge based systems; Power generation; Uncertainty;
Conference_Titel :
Information Reuse and Integration, 2004. IRI 2004. Proceedings of the 2004 IEEE International Conference on
Print_ISBN :
0-7803-8819-4
DOI :
10.1109/IRI.2004.1431531
