DocumentCode
1560778
Title
Breeder genetic algorithm based fuzzy simulation
Author
Zhang, Qianli ; Li, Xing ; Tran, Quang-anh
Author_Institution
CERNET Center, Tsinghua Univ., Beijing, China
Volume
3
fYear
2004
Firstpage
2109
Abstract
Fuzzy simulation is often required in fuzzy programming. In this paper, we propose the application of breeder genetic algorithm (BGA) to compute possibility and find critical values. BGA is a kind of genetic algorithm, which is especially powerful and reliable in global searching. Experiments show that BGA based fuzzy simulation has a better performance.
Keywords
fuzzy set theory; genetic algorithms; mathematical programming; breeder genetic algorithm; fuzzy programming; fuzzy simulation; global searching; Computational modeling; Fuzzy neural networks; Fuzzy systems; Genetic algorithms; Genetic programming; Mathematical model; Mathematical programming; Power engineering and energy; Power engineering computing; Reliability engineering;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Control and Automation, 2004. WCICA 2004. Fifth World Congress on
Print_ISBN
0-7803-8273-0
Type
conf
DOI
10.1109/WCICA.2004.1341957
Filename
1341957
Link To Document