基于LIBSVM和时间序列的区域货运量预测研究  

Research of regional freight volume forecasting based on LIBSVM and time series

作　　者：曾鸣[1] 林磊[2] 程文明[1] 

机构地区：[1]西南交通大学机械工程学院,成都610031 [2]纽约州立大学布法罗分校土木工程学院,美国布法罗14260

出　　处：《计算机工程与应用》2013年第21期6-10,共5页Computer Engineering and Applications

基　　金：国家留学基金委建设高水平大学研究生项目专项资金资助(留金发[2012]3013)

摘　　要：针对区域货运量预测中影响因素多、样本数量小的问题,提出了互信息MI与LIBSVM支持向量回归以及状态空间时间序列相结合的预测方法,采用MI进行高维度特征降维后,以新的低维空间作为样本输入,分别建立LIBSVM支持向量回归和状态空间时间序列预测模型。通过重庆市货运量预测实验结果及对比分析表明,该方法在进行有效预测的同时能够改善预测精度,相对误差约为0.06。To the problem of excessive affecting factors and small sample size in regional freight volume forecasting, the LIBSVM support vector regression model and state space time series model with mutual information technique are proposed. In this approach, the MI is adopted to reduce the dimensionality of the high dimensional features, and then the new lower dimensional subspace is treated as the sample input to establish the LIBSVM support vector regression model and the state space time series model. The experimental results of Chongqing freight volume forecasting and comparative analysis show that the method can improve the prediction accuracy while accomplishing a valid forecast, and the relative error is about 0.06.

关 键 词：互信息(MI) 支持向量机程序库(LIBSVM)支持向量回归 状态空间时间序列 区域货运量 预测 

分 类 号：U491.14[交通运输工程—交通运输规划与管理]