DocumentCode
1961572
Title
A New Implementation of Population Based Incremental Learning Method for Optimization Studies in Electromagnetics
Author
Yang, S.Y. ; Ho, S.L. ; Ni, G.Z. ; Machado, José Márcio ; Wong, K.F.
Author_Institution
Coll. of Electr. Eng., Zhejiang Univ., Hangzhou
fYear
0
fDate
0-0 0
Firstpage
163
Lastpage
163
Abstract
To enhance the global search ability of population based incremental learning (PBIL) methods, it is proposed that multiple probability vectors are to be included on available PBIL algorithms. As a result, the strategy for updating those probability vectors and the negative learning and mutation operators are redefined as reported. Numerical examples are reported to demonstrate the pros and cons of the newly implemented algorithm
Keywords
electromagnetic forces; genetic algorithms; learning (artificial intelligence); search problems; electromagnetics; global search; multiple probability vectors; mutation operators; negative learning; population based incremental learning method; Algorithm design and analysis; Biological cells; Convergence; Genetic algorithms; Genetic mutations; Learning systems; Optimization methods; Power transformers; Proposals; Sampling methods;
fLanguage
English
Publisher
ieee
Conference_Titel
Electromagnetic Field Computation, 2006 12th Biennial IEEE Conference on
Conference_Location
Miami, FL
Print_ISBN
1-4244-0320-0
Type
conf
DOI
10.1109/CEFC-06.2006.1632955
Filename
1632955
Link To Document