Applied Research of Pantograph Carbon Slide Formulation Optimization Based on Genetic Neural Network

Ze Heng He; Xiu Yan Cai; Jing Hu; Yu Zhang; Yue Wang

doi:10.4028/www.scientific.net/AMR.466-467.411

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 466-467Applied Research of Pantograph Carbon Slide...

Applied Research of Pantograph Carbon Slide Formulation Optimization Based on Genetic Neural Network

Abstract:

Applying BP neural network improved by GA to build a nonlinear multi-objective model between formulation ingredient and mechanical properties of electric locomotive pantograph carbon slide. And on the basis of test data improved neural network is trained; finally we can get a genetic neural network model. Therefore, when given specific formulation of carbon slide plate, it is able to predict the corresponding mechanical properties. The research shows that the trained genetic neural network can accurately predict relevant properties of carbon slide plate and be confirmed the practical significance of the algorithm.

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Periodical:

Advanced Materials Research (Volumes 466-467)

Pages:

411-415

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.466-467.411

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Online since:

February 2012

Authors:

Ze Heng He, Xiu Yan Cai, Jing Hu, Yu Zhang, Yue Wang

Keywords:

BP Neural Network (BPNN), Formulation Optimization, Genetic Algorithm (GA), Pantograph Carbon Slide

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