Title :
Generating fuzzy rules by genetic algorithms
Author :
Mohammadian, M. ; Stonier, R.J.
Author_Institution :
Dept. of Comput. Sci., Edith Cowan Univ., Perth, WA, Australia
Abstract :
A general method is developed to generate fuzzy rules by using genetic algorithms (GAs) and a fuzzy logic controller (FLC). By using GAs as a learning procedure and a FLC as the system´s performance evaluator, the proposed architecture can construct an input-output mapping in the form of fuzzy if-then rules. The performance of the new architecture is compared with an artificial neural networks controller and pure limited-rule fuzzy rule controller for the truck back-upper problem
Keywords :
fuzzy control; fuzzy logic; genetic algorithms; learning systems; road vehicles; fuzzy logic controller; fuzzy rules generation; genetic algorithms; input-output mapping; learning procedure; system performance evaluator; truck back-upper problem; Artificial neural networks; Data mining; Fuzzy control; Fuzzy logic; Fuzzy neural networks; Fuzzy sets; Fuzzy systems; Genetic algorithms; Genetic mutations; Humans;
Conference_Titel :
Robot and Human Communication, 1994. RO-MAN '94 Nagoya, Proceedings., 3rd IEEE International Workshop on
Conference_Location :
Nagoya
Print_ISBN :
0-7803-2002-6
DOI :
10.1109/ROMAN.1994.365902
