期刊名称：International Journal of Hybrid Information Technology
印刷版ISSN：1738-9968
出版年度：2016
卷号：9
期号：2
页码：215-226
DOI：10.14257/ijhit.2016.9.2.19
出版社：SERSC
摘要：In this paper, we first comparative analysis the existing prediction methods. Based on the GM and ARMA, we propose a new combined forecasting model which integrated the advantage of the GM is suitable for medium and long term forecast, the GM algorithm is simple and the ARMA is suitable for short time forecast. Moreover, we use the rail traffic data to verify this model. The results show that the combined forecasting model we proposed is of high forecast precision, and the combined forecasting model is better than the single forecasting model.
