Title :
Risk assessment model of error in aviation maintenance based on integrated neural networks
Author :
Xiao, Li-Zhi ; Sun, De-Xiang ; Xing, Guo-Ping ; Huang, Yong
Author_Institution :
Dept. of Inf. Countermeasure, Aviation Univ. of Air Force, Changchun, China
Abstract :
Use the integrated neural networks to evaluate the risk of error in aviation maintenance. First of all, establishes the evaluation index system for error in aviation maintenance, then proposals an evaluation model based on neural networks which has the function of risk assessment after training, finally the evaluation results will be achieved via the parameters. The sample sets of training network can be summarized by experts from previous data of similar risk assessment processes. The simulation results show that the methods will reduce the influence of human factor and make the solution more objective and creditable.
Keywords :
aerospace computing; aircraft maintenance; human factors; neural nets; risk management; aviation maintenance error; evaluation index system; human factor; integrated neural networks; risk assessment model; Biological neural networks; Indexes; Maintenance engineering; Risk management; Training; Transfer functions; integrated neural networks; maintenance error; risk assessment;
Conference_Titel :
Quality, Reliability, Risk, Maintenance, and Safety Engineering (ICQR2MSE), 2011 International Conference on
Conference_Location :
Xi´an
Print_ISBN :
978-1-4577-1229-6
DOI :
10.1109/ICQR2MSE.2011.5976691
