摘要(英) |
Railway transport is the most reliable system in the land transportation system, but it may cause serious effect while the accidents happen. According to the Taiwan Railway Administration’s former statistic data, rolling stock accident accounted for above 40% of the overall rail accidents which closely related to the passenger. Therefore, the purpose of the study aims to establish rolling stock breakdowns analysis model to predict the future accidents. The study collecting the Taiwan Railway Administration five years of accident data from 2010 to 2014, using general linear models of Poisson and Negative Binomial Regression, in relation to railway travel characteristics, track geometry and so forth. Constructing the railway accident frequency model and failed mode to predict accident in the future. .
The result indicated that railway accidents’ frequency model and failed model are suitable to using Poisson Regression is better than Binomial Regression to predict accidents in the future. The peak/off-peak hours and rush /general hours under different loading conditions have significant influence on accident. |
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