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Highway Tunnel Traffic Accidents Prediction Model Based on BP Neural Network

机译:基于BP神经网络的公路隧道交通事故预测模型。

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摘要

A prediction model of China's highway tunnel traffic accidents is established, on the basis of the characteristics of BP neural network, such as auto-study, auto-organization and auto-ability. Using the grey relational theory, major influencing factor index of the highway tunnel traffic accidents are chosen, and key technologies of the construction of BP neural network predictive are also discussed . Then, the model is trained and tested using the statistics data of China's highway tunnel traffic accident from 1995 to 2008 . The results show that the precision of this prediction model is high, so that it could be applied to forecasting highway tunnel traffic accidents.
机译:根据自动学习,自动组织,自动能力等BP神经网络的特点,建立了我国公路隧道交通事故预测模型。运用灰色关联理论,选择了公路隧道交通事故的主要影响因素指标,并探讨了BP神经网络预测构造的关键技术。然后,利用1995年至2008年中国公路隧道交通事故统计数据对模型进行训练和检验。结果表明,该预测模型的精度较高,可用于公路隧道交通事故的预测。

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