Modeling nonlinear relationship between crash frequency by severity and contributing factors by neural networks
发布时间：2016-04-27
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发表刊物：Analytic Methods in Accident Research
摘要：This study develops neural network models to explore the nonlinear relationship between crash frequency by severity and risk factors. To eliminate the possibility of over-fitting and to deal with black-box characteristic, a network structure optimization and a rule extraction method are proposed. A case study compares the performance of the modified neural network models with that of the traditional multivariate Poisson-lognormal model for predicting crash frequency by severity on road segments in Hong Kong. The results indicate that the trained and optimized neural networks have better...
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合写作者：Wong S.C. (2016), Pei X., Huang H.*, Zeng Q.
是否译文：否
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