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Vol. 159, Issue 11, November 2013, pp. 132-137

 

Bullet

 

ANN RBF Based Approach of Risk Assessment for Aviation ATM Network
 
1 Lan Ma, 2 Deng Pan, 3 Zhijun Wu

School of Air Traffic Management, Civil Aviation University of China, Tianjin, P. R. China, 300300
Tel.: 24092430, fax: 24092431
E-mail: malan66@263.net, pandeng19@163.com, zjwu@cauc.edu.cn

 

Received: 13 September 2013   /Accepted: 25 October 2013   /Published: 30 November 2013

Digital Sensors and Sensor Sysstems

 

Abstract: ATM (Asynchronous Transfer Mode) network is the core communication network of civil aviation aeronautical telecommunication network. So it is an urgent time to do scientific risk assessment for ATM network as soon as possible. According to threats and vulnerabilities existing in ATM network, which could bring bad influence to assets and missions of ATM network, even threaten the whole security situation of ATM network. This paper proposes risk assessment model based on RBF neural network. According to the established evaluation model, indexes that influencing the security situation of missions are used as input of the model and train the model. The well-trained neural network model is used to assess ATM network, while the results are compared to that of the traditional methods of scoring by experts for rounds of times. The experimental results demonstrate that the risk assessment model has strong capacities of self-learning and convergence, accords well with the complex ATM network for risk assessment.

 

Keywords: RBF neural network, ATM network, Risk assessment, MATLAB, Evaluation model.

 

 

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