Title :
Extension Genetic Algorithm and Its Applications
Author :
Wang, Meng-Hui ; Tseng, Yi-Feng ; Chen, Hong-Cheng ; Chao, Kuei-Hsiang
Author_Institution :
Dept. of Electr. Eng., Nat. Chin-Yi Univ. of Technol., Taiping
Abstract :
This paper presents a novel classified method that is called extension genetic algorithm (EGA). The new method is a combination of extension theory and genetic algorithm (GA). In the past, we used the extension method in some clustered problems. With the method, we had to rely on experiences to set rules on classical domain and weight, which caused to increase two tedious and complicated steps in clustering process. In order to improve this defect, the paper uses the EGA to find the best parameter of classical domain. Through the simulations, we prove that this new method can eliminate try and error adjustment of modeling parameters and increase accuracy of the classification.
Keywords :
genetic algorithms; pattern classification; pattern clustering; classification method; clustering process; extension genetic algorithm; Artificial intelligence; Chaos; Expert systems; Fault diagnosis; Fuzzy logic; Fuzzy neural networks; Genetic algorithms; Multidimensional systems; Neural networks; Training data;
Conference_Titel :
Innovative Computing Information and Control, 2008. ICICIC '08. 3rd International Conference on
Conference_Location :
Dalian, Liaoning
Print_ISBN :
978-0-7695-3161-8
Electronic_ISBN :
978-0-7695-3161-8
DOI :
10.1109/ICICIC.2008.270