Application Research on Machine Learning and Statistical Forecasting Algorithm in Traffic Information Forecasting System

摘要：

This paper proposes an algorithm model based on the machine learning and statistic forecasting method to forecast the traffic information. It constructs the forecasting specimens set by the mechanism learning of the machine learning, forecasts the short time traffic information by the data fit return technology, and constructs the knowledge base, which uses the concept of knowledge maturation degree to judge the application probability rate of the forecasted information in the traffic information forecasting system. It implements the short time traffic flowing forecasting in the traffic information forecasting system by this algorithm model, and it gets the effective to forecast the change of the traffic flowing state on some routes or transport corridor in the few minutes of the future.

关键词： mechanism learning data fit knowledge maturation degree traffic information forecasting

作者: Yan Pei Guang-ming Yang

作者单位: Software School, Northeastern University Shenyang, China

会议类型: 国际会议

会议名称: 2009 Ninth International Conference on Hybrid Intelligent Systems(第九届混合智能系统国际会议 HIS 2009)

会议地点: 沈阳

会议语种:英文

页码: 1-6

在线出版日期: 2009-08-12（万方平台首次上网日期，不代表论文的发表时间）