ANN RBF Based Approach of Risk Assessment for Aviation ATM Network

• Main Authors: Lan Ma, Deng Pan, Zhijun Wu
• Format: Article
• Language: English
• Published: IFSA Publishing, S.L. 2013-11-01
• Series: Sensors & Transducers
• Subjects: RBF neural network; ATM network; Risk assessment; MATLAB; Evaluation model.
• Online Access: http://www.sensorsportal.com/HTML/DIGEST/november_2013/PDF_vol_159/P_1548.pdf
• ISSN: 2306-8515; 1726-5479

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.