Research on BA-WNN based safety risk early warning method of taxiway in airport

doi:10.16265/j.cnki.issn1003-3033.2017.08.023

China Safety Science Journal ›› 2017, Vol. 27 ›› Issue (8): 132-137.doi: 10.16265/j.cnki.issn1003-3033.2017.08.023

• Safety Science of Engineering and Technology • Previous Articles Next Articles

Research on BA-WNN based safety risk early warning method of taxiway in airport

LIU Junyong¹, GAO Shu^1,2, LUO Fan³, WEI Wanqi¹

1 School of Computer Science and Technology, Wuhan University of Technology, Wuhan Hubei 430063, China;
2 Hubei Key Laboratory of Transportation Internet of Things, Wuhan University of Technology,Wuhan Hubei 430063,China;
3 School of Management, Wuhan University of Technology, Wuhan Hubei 430070, China

Received:2017-04-28 Revised:2017-07-03 Online:2017-08-20 Published:2020-10-13

Abstract

Abstract: For the sake of finding a more effective solution to safety risk early warning of taxiway in the airport, WNN was chosen as the main method for realizing the safety risk early warning of taxiway. Seeing that the training process of WNN is easy to fall into local optimum and the training is unstable, BA was used to optimize WNN. A BA-WNN based safety risk early warning method of taxiway in the airport was worked out. An effectiveness comparison was made between BPNN, WNN and GA-WNN and BA-WNN method. The results show that BA-WNN has the highest accuracy rate of 84%, and a low false alarm rate under all working conditions.

Key words: risk early warning, early warning indicators, taxiway, bat algorithm (BA), wavelet neural network (WNN)

CLC Number:

X949

LIU Junyong, GAO Shu, LUO Fan, WEI Wanqi. Research on BA-WNN based safety risk early warning method of taxiway in airport[J]. China Safety Science Journal, 2017, 27(8): 132-137.

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Research on BA-WNN based safety risk early warning method of taxiway in airport

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