基于移动优化灰色马尔科夫的道路交通事故预测

Prediction of Road Traffic Accidents based on Rolling Optimization Grey Markov

针对事故预测精度受预测数据时效性影响问题,引入移动优化策略,建立移动优化灰色马尔科夫动态预测模型.用灰色预测来揭示道路交通事故发展变化趋势,通过马尔科夫预测发掘状态间的转移规律,从而提高随机性时间序列的预测精度.案例分析表明,提出的方法在一定时段内具有较好的预测精度和实用性,可为道路交通事故预测分析及交通安全预警提供参考.

In order to solve the problem that the accuracy of accident prediction affected by the timeliness of base data,the dynamic prediction model rolling optimization-grey Markov is established by introducing the rolling optimization strategy.Grey prediction method is used to reveal the development trend of s road traffic accidents,and Markov method is used to predict the transfer law between excavated states,so as to improve the prediction accuracy of random time series.The case study shows that the proposed method has good prediction accuracy and practicability in a certain period of time,which can provide reference for road traffic accident prediction analysis and traffic safety early warning.