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A Pseudo-Parallelism Genetic Algorithm Framework to Optimization of Neural Networks

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3 Author(s)
Shu-hai Zhao ; Sch. of Manage., Univ. of JiNan, Jinan ; Li Shao ; Jin-zhu Ma

This paper present a new approach, combined pseudo- parallelism evolution technique based on sub-population competition with parent mutation mechanism, for automatic topology optimization of multilayer feedforward neural networks. It allows that two networks with different number of individuals can be crossed to a new valid "child" network. The calculation result of an example shows that PPGA is able to get the real-time information of population diversity during the process of evolution and has some improvements in both global converging velocity and searching precision.

Published in:

Intelligent Systems and Applications, 2009. ISA 2009. International Workshop on

Date of Conference:

23-24 May 2009

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