中文摘要：

采用持向量机方法构建了居民出行方式选择模型,使用网格搜索方法选择支持向量参数,避免参数选择的随机性,分析不同核函数对模型构建的影响。研究表明,采用多项式核函数、RBF核函数构建的支持向量机模型对居民出行方式预测精度较高,所构建的模型可用于居民出行方式预测;在支持向量机核函数选择中,优先选择RBF核函数,其次为多项式核函数。

英文摘要：

This paper adopts support vector machine method to construct option model of residents＇ trip,and uses grid-search method to select parameters.This method avoids the randomness in choosing the parameters.Then it analyzes the influence of different kernel function to SVM model.The result shows that the support vector machines with polynomial kernel functions and RBF kernel functions obtain high accuracy in trip mode prediction.The constituted model can be used for residents＇ trip forecasting.In the choice of support vector machine kernel function,RBF kernel function is the privilege,polynomial kernel function is the followed.