基于遗传算法优化BP神经网络的道口事故预测

针对铁路事故发生的偶然性和事故发生原因的复杂性，提出应用BP神经网络对铁路事故进行较长期预测的建议，并以美国高速公路-铁路道口事故为实例，应用BP神经网络方法和遗传算法优化的BP神经网络方法对美国高速公路—铁路道口未来3年的事故进行预测，并将预测结果进行对比，结果表明，遗传算法优化的BP神经网络可以用于铁路事故的中长期预测。

Prediction on crossing accident based on BP neural network of optimized Genetic Algorithm

According to the unpredictability and the complexity of the railway accidents happening, the suggestions using the BP neural network to predict the railway accidents during a long period were presented. And taking the USA highway-railway crossing accidents as examples, the American highway-railway crossing accident in the next three years were forecasted using the BP neural network method and the BP neural network method optimized by the Genetic Algorithm. The forcasted results obtained using the two methods were compared. It was shown that, the BP neural network method optimized by the Genetic Algorithm could be used for the railway accident long-term prediction. In 2014, from January to April and from October to December, and in the whole 2015, was the periods that the USA highway-railway crossing accidents happening frequently.