A new implementation of Population Based Incremental Learning method for optimization studies in electromagnetics
| Contribuinte(s) |
Universidade Estadual Paulista (UNESP) |
|---|---|
| Data(s) |
27/05/2014
27/05/2014
21/11/2006
|
| Resumo |
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. |
| Identificador |
http://dx.doi.org/10.1109/CEFC-06.2006.1632955 12th Biennial IEEE Conference on Electromagnetic Field Computation, CEFC 2006. http://hdl.handle.net/11449/69227 10.1109/CEFC-06.2006.1632955 2-s2.0-42749107739 |
| Idioma(s) |
eng |
| Relação |
12th Biennial IEEE Conference on Electromagnetic Field Computation, CEFC 2006 |
| Direitos |
closedAccess |
| Palavras-Chave | #Algorithms #Learning systems #Numerical analysis #Optimization #Probability #Vectors #Multiple probability vectors #Population Based Incremental Learning (PBIL) #Electromagnetism |
| Tipo |
info:eu-repo/semantics/conferencePaper |
