This paper addresses the characteristics of urban rail transit fires and proposes a predictive model combining evacuation simulation and random forests for rapid forecasting of evacuation targets. Firstly, the characteristics of urban rail transit fires and key factors affecting evacuation are analyzed. Secondly, a three-dimensional model for crowd evacuation simulation is constructed. Finally, a predictive model based on random forests is developed, with an analysis of the importance of predictive variables. The random forest approach can effectively deal with complex nonlinear relationships and large amounts of data, and improve the prediction accuracy and robustness of the model. The results indicate that this method can rapidly predict emergency evacuation scenarios in urban rail transit fires, achieving an accuracy of 95%.
Analysis of Fire Characteristics and Emergency Evacuation Influencing Factors in Urban Railway Transportation
Advances in Engineering res
International Symposium on Traffic Transportation and Civil Architecture ; 2024 ; Tianjin, China June 21, 2024 - June 23, 2024
Proceedings of the 2024 7th International Symposium on Traffic Transportation and Civil Architecture (ISTTCA 2024) ; Chapter : 84 ; 874-881
2024-09-24
8 pages
Article/Chapter (Book)
Electronic Resource
English
Simulating Passenger Evacuation in Railway Station under Fire Emergency using Safe Zone Approach
Transportation Research Record | 2020
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