Optimizing Design and Application of BP Neural Networks Based on Genetic Algorithm

Wang Jie Niu; Er Guang Qu; Chun Yan Liu

doi:10.4028/www.scientific.net/AMR.317-319.245

Paper Titles

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Study on the Stress-Strain Distribution Rule of the Cylindrical Part Deep Drawing with Prefabricate-Holes
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The Core of Engineering Education Is to Cultivate the Students’ Engineering Practical Ability
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Optimizing Design and Application of BP Neural Networks Based on Genetic Algorithm
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Investigation of Consumer-Oriented Product System Design
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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 317-319Optimizing Design and Application of BP Neural...

Optimizing Design and Application of BP Neural Networks Based on Genetic Algorithm

Abstract:

Genetic algorithm optimize weight’s volume of Neural Networks by optimizing learning rate and inertia coefficient, which overcome the BP algorithmic shortcoming of easy into the part extreme, and have ensured BP algorithmic training accuracy, and makes it have higher self-adaptability and self-learning ability.

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Periodical:

Advanced Materials Research (Volumes 317-319)

Pages:

245-249

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.317-319.245

Citation:

Cite this paper

Online since:

August 2011

Authors:

Wang Jie Niu, Er Guang Qu, Chun Yan Liu

Keywords:

Genetic Algorithm (GA), Neural Network (NN), Optimise

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