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Please use this identifier to cite or link to this item: http://acervodigital.unesp.br/handle/11449/69227
Title: 
A new implementation of Population Based Incremental Learning method for optimization studies in electromagnetics
Author(s): 
Institution: 
  • Zhejiang University
  • Hong Kong Polytechnic University
  • Universidade Estadual Paulista (UNESP)
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. ©2006 IEEE.
Issue Date: 
21-Nov-2006
Citation: 
12th Biennial IEEE Conference on Electromagnetic Field Computation, CEFC 2006.
Keywords: 
  • Algorithms
  • Learning systems
  • Numerical analysis
  • Optimization
  • Probability
  • Vectors
  • Multiple probability vectors
  • Population Based Incremental Learning (PBIL)
  • Electromagnetism
Source: 
http://dx.doi.org/10.1109/CEFC-06.2006.1632955
URI: 
Access Rights: 
Acesso restrito
Type: 
outro
Source:
http://repositorio.unesp.br/handle/11449/69227
Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

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