Evaluation of Support Capability of CAPF ArmouredVehicle with Improved BP Neural Network
Received date: 2015-10-16
Revised date: 2015-11-17
Online published: 2016-07-30
There are many factors affecting security of Chinese armed police force (CAPF) armored vehicles in wartime and peacetime. To overcome ambiguity and uncertainty in the evaluation of security capability of CAPF armored vehicles, this paper establishes an evaluation index system using glowworm swarm to optimize a BP neural network. Having determined the initial weights and thresholds, a security of CAPF armored vehicles is evaluated. By establishing a model, calculation and analysis are performed. It is concluded that the glowworm swarm optimization BP (GSOBP) neural network converges fast and is accurate. The method can be used effectively for evaluating security of the CAPF wheeled armored anti-riot vehicles.
SHAN Ning, BAN Chao, DENG Chun-ze . Evaluation of Support Capability of CAPF ArmouredVehicle with Improved BP Neural Network[J]. Journal of Applied Sciences, 2016 , 34(4) : 461 -468 . DOI: 10.3969/j.issn.0255-8297.2016.04.011
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