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

fYear

2011

fDate

17-19 June 2011

Firstpage

633

Lastpage

636

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;

fLanguage

English

Publisher

ieee

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

Type

conf

DOI

10.1109/ICQR2MSE.2011.5976691

Filename

5976691