Title: Electric vehicle industry development environment evaluation in China based on BP neural network

Authors: Chuansheng Xie; Chenchen Zhao; Dapeng Dong; Pengyuan Zhong

Addresses: School of Economics and Management, North China Electric Power University, Changping District, Beijing 102206, China ' School of Economics and Management, North China Electric Power University, Changping District, Beijing 102206, China ' School of Economics and Management, North China Electric Power University, Changping District, Beijing 102206, China ' School of Economics and Management, North China Electric Power University, Changping District, Beijing 102206, China

Abstract: As an emerging industry of energy conservation and environment protection, electric vehicle industry has broad prospects for development. But now, electric car industry is in the initial stage and the development environment is complex, so it is very necessary to study the development environment. This paper combines electric vehicle industry development environment evaluation index system with BP neural network to establish the electric vehicle industry evaluation model. Then the indicator score values as training samples obtained from the use of experts scoring method are imported to the BP neural network evaluation model. After training and testing the neural network, this paper compares the testing results with the results based on analytic hierarchy process (AHP) and fuzzy comprehensive evaluation method, to test the validity of the evaluation model. The result shows that evaluation model based on BP neural network can effectively improve the reliability and accuracy of evaluation result.

Keywords: electric vehicles; BP neural networks; backpropagation; environmental evaluation; simulation; process modelling; China; analytical hierarchy process; AHP; comprehensive evaluation; fuzzy evaluation; fuzzy logic.

DOI: 10.1504/IJSPM.2014.066355

International Journal of Simulation and Process Modelling, 2014 Vol.9 No.4, pp.234 - 239

Received: 14 Sep 2012
Accepted: 29 Oct 2013
Published online: 30 Apr 2015 *

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