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A new implementation of Population Based Incremental Learning method for optimization studies in electromagnetics

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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.

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Algorithms, Learning systems, Numerical analysis, Optimization, Probability, Vectors, Multiple probability vectors, Population Based Incremental Learning (PBIL), Electromagnetism

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English

Citation

12th Biennial IEEE Conference on Electromagnetic Field Computation, CEFC 2006.

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