DocumentCode
2662906
Title
Population optimization algorithm based on ICA
Author
Qingfu Zhang ; Allinson, Ngel M. ; Yin, Hujun
Author_Institution
Dept. of Electr. Eng. & Electron., Univ. of Manchester Inst. of Sci. & Technol., UK
fYear
2000
fDate
2000
Firstpage
33
Lastpage
36
Abstract
We propose a new population optimization algorithm called univariate marginal distribution algorithm with independent component analysis (UMDA/ICA). Our main idea is to incorporate ICA into the UMDA algorithm in order to tackle the interrelations among variables. We demonstrate that UMDA/ICA performs better than UMDA for a test function with highly correlated variables
Keywords
genetic algorithms; principal component analysis; ICA; UMDA algorithm; genetic algorithms; highly correlated variables; independent component analysis; population optimization algorithm; univariate marginal distribution algorithm; variable interrelations; Algorithm design and analysis; Approximation algorithms; Computational efficiency; Electronic design automation and methodology; Evolution (biology); Genetic mutations; Independent component analysis; Performance analysis; Probability distribution; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Combinations of Evolutionary Computation and Neural Networks, 2000 IEEE Symposium on
Conference_Location
San Antonio, TX
Print_ISBN
0-7803-6572-0
Type
conf
DOI
10.1109/ECNN.2000.886216
Filename
886216
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