摘要
运用主成分回归分析法,将影响公路客运量的众多相关因素简化为少数不相关因素,消除因变量过多导致的多重共线性,可构建公路客运量预测模型。实例证明,该模型具有较高的精度,适合影响因素指标发展较为明确的客运量短期预测。
Using the method of the regression of principal components analysis can simplify the numerous correlation factors affecting highway passenger transport volume to the minority non-correlated factor, in order to eliminate muhi-colinearity because of excessively many variables, and the forecast model of highway passenger transport volume is established. The instance indicates that the highway passenger transport volume forecast models embodies the high precision can be applied in short-term highway passenger transport volume forecast with the more explicit development.
出处
《交通标准化》
2009年第9期77-81,共5页
Communications Standardization
关键词
主成分回归
多重共线性
客运量预测
principle component analysis in regression
muhi-colinearity
passenger transport volume forecast
