Title
Fitting fuzzy membership functions using genetic algorithms
Abstract
The use of Fuzzy Logic to solve control problems have been increasing considerably in the past years. This makes the teaching of Fuzzy Control in engineering courses an urgent need. So, a self-training computer package in fuzzy control theory for students was developed before. The package has all necessary instructions for understanding of all principles of fuzzy control by the users. The training instructions are given through an application drill. Though this approach proved to be an effective one, in giving to the students a way to understand an actual situation, it has a limitation: the learning method itself. The students always use the "try-and-error" method to arrive to an adequate control action. The problem with this method is that students may be driven to the wrong conclusion that fuzzy control system corrections are but a matter of supposition. The purpose of this paper is to present a strategy for the membership functions automatic adjustment using genetics algorithms.
Year
DOI
Venue
2000
10.1109/ICSMC.2000.885022
IEEE International Conference on Systems Man and Cybernetics Conference Proceedings
Keywords
Field
DocType
membership function,chemical industry,packaging,application software,fuzzy logic,fuzzy control,genetic algorithm,genetic algorithms
Fuzzy classification,Defuzzification,Fuzzy set operations,Computer science,Fuzzy logic,Artificial intelligence,Fuzzy Control Language,Fuzzy control system,Fuzzy number,Type-2 fuzzy sets and systems,Machine learning
Conference
ISSN
Citations 
PageRank 
1062-922X
1
0.37
References 
Authors
1
4
Name
Order
Citations
PageRank
Germano Lambert-torres15919.17
Marcelo A. Carvalho221.23
l e b da silva310.37
João O. P. Pinto472.96