Citation

Hu L, He Y, She T, Meng L, Yang J. China Saf. Sci. J. 2019; 29(5): 145-150.

Copyright

(Copyright © 2019, China Occupational Safety and Health Association, Publisher Gai Xue bao)

DOI

10.16265/j.cnki.issn1003-3033.2019.05.024

PMID

unavailable

Abstract

In order to improve the emergency rescue system for expressway traffic accidents, Kunshi expressway was taken as an example, GA was combined with BP neural network model, and GA-BP neural network model was used to identify the highway accidents prone location. According to the Kunshi expressway environmental conditions, the candidate points for the emergency rescue base were selected. The bi-level programming theory model was applied to analyze the location of the Kunshi expressway emergency rescue base, and the firefly algorithm was used to optimize the solution. Then the optimal layout plan for the location of the emergency rescue base of Kunshi expressway was obtained. The results show that the GA-BP neural network model is more accurate in identifying the faulty section of expressway than the traditional model, and that the bi-level planning model and the firefly algorithm can be used to identify the best location of the Kunshi expressway emergency rescue center. © 2019 China Safety Science Journal

Language: zh