铁道科学与工程学报2017，Vol.14Issue(11)：2480-2486,7.
基于小波灰色GM(1,1)模型的货运量预测研究
Railway freight volume forecasting based on grey GM(1,1) model and wavelet de-noising
摘要
Abstract
As the main artery of the national economy, railway freight volume forecasting is of great significance to formulate development strategy of railway transportation and improve efficiency of railway transport facilities. In order to improve the forecasting precision of railway freight volume, this paper studied how to remove the noise of the experimental data in order to improve the smoothness of the original sequence by using wavelet analysis method. The improved grey GM(1,1) model that is used to predict the newly generated sequences eliminated the inherent deviation of traditional grey GM(1,1) model. By forecasting the railway freight volume from 1990 to 2014, the results show that compared with traditional grey GM(1,1) model, the prediction of the improved model is more accurate and effective.关键词
铁路货运量/灰色GM(1,1)模型/小波降噪/预测Key words
railway freight volume/grey GM(1,1)model/wavelet de-noising/forecasting分类
交通工程引用本文复制引用
崔乃丹,向万里,孟学雷,张春民,张博昊..基于小波灰色GM(1,1)模型的货运量预测研究[J].铁道科学与工程学报,2017,14(11):2480-2486,7.基金项目
国家自然科学基金资助项目(61563028,61364026) （61563028,61364026）
教育部人文社会科学研究一般资助项目(15YTAZ106) （15YTAZ106）
