Dynamic Grey Markov Model for Forecasting Railway Train Accidents

摘要：

To predict railway train accidents, dynamic processing of the original data series was dealt with by appending the latest information and removing the oldest at the same time based on grey forecasting model. Thus, the dynamic grey forecasting model was set up. Then combined with the markov model, the dynamic grey markov model was established. A method of states division had been adopted in which the states of the original data were determined according to their central tendency curve. This method overcame the defects of the blindness and subjectivity in other previous divisions. The dynamic grey markov model was tried to apply to predict the number of railway train accidents. The result indicates that the forecasting value of dynamic grey markov model has a better fit with actual value and higher prediction accuracy. It can be used to predict railway train accidents.

关键词： railway train accidents dynamic forecasting grey markov model central tendency curve of the original data

作者: LI Bo MI Huali

作者单位: College of Civil and Safety Engineering, Dalian Jiao Tong University, Dalian 116028, Liaoning, China

会议类型: 国际会议

会议名称: The 2010 International Symposium on Safety Science and Technology(2010 安全科学与技术国际会议)

会议地点: 杭州

会议语种:英文

页码: 1994-1999

在线出版日期: 2010-10-26（万方平台首次上网日期，不代表论文的发表时间）