Nuclear Techniques ›› 2020, Vol. 43 ›› Issue (2): 20602-020602.doi: 10.11889/j.0253-3219.2020.hjs.43.020602

• NUCLEAR ENERGY SCIENCE AND ENGINEERING • Previous Articles     Next Articles

Evaluation study on comprehensive efficiency of physical protection system based on neural network

Gou ZHAO1,Hanlin XIONG1(),Guodong WU1,Yukun MA2,Fanfu KONG1   

  1. 1. Wuhan Second Ship Design Institute, Wuhan 430064, China
    2. China Shipbuilding Industry Group Co. , Ltd. , Beijing 100097, China
  • Received:2019-10-09 Revised:2019-12-19 Online:2020-02-15 Published:2020-02-24
  • Contact: Hanlin XIONG E-mail:514404908@qq.com
  • About author:ZHAO Gou, male, born in 1990, graduated from Nanjing University of Science and Technology with a master's degree in 2015, focusing on physical protection technology of nuclear facilities

Abstract: Background

At present, most of the physical protection systems of nuclear facilities at home and abroad use the path analysis method to evaluate the effectiveness. The performance of the system is evaluated by calculating the cut off probability, hence the evaluation index is single and cannot reflect factors such as the system reliability, the command strategy, the information security design and other factors.

Purpose

This study aims to analyze the comprehensive effectiveness of the physical protection system by using neural network method.

Methods

The comprehensive effectiveness evaluation index system of the physical protection system was established by using the analytic hierarchy process (AHP), and the comprehensive effectiveness evaluation model of the physical protection system for nuclear facilities was established by using the composite ability of the nonlinearity of the BP (back propagation) neural network. The comprehensive effectiveness of the physical protection system for the marine nuclear power platform was evaluated.

Results & Conclusions

The evaluation results show that the BP neural network evaluation model converges fast, avoids the shortcomings of the majority of sample concentration effects in the AHP evaluation process, and has better adaptability and stability. It provides a kind of field for physical protection effectiveness evaluation.

Key words: Physical protection, Comprehensive effectiveness evaluation, Analytic hierarchy process, Artificial neural network

CLC Number: 

  • TL364.1