基于C-SVM分类器对影响乘客选择出行方式的模型建立与求解

Establishing and solving the model based on C-SVM classifier to influence passenger’s choice travel mode

随着我国铁路技术的高速发展,高速铁路的里程已经超过20000 km,高速铁路可以减少人们出行时间以及增加乘客乘车舒适度等优势。因此,越来越多的人选择高速铁路出行。对于大学生而言,铁路运输是假期回家不可缺少的交通方式,选择乘高铁回家的学生越来越多。但由于种种因素,还是会有学生选择乘普通火车回家。考虑到影响学生搭乘高铁和普通火车的因素较复杂并有较大的研究空间,故文章将对此进行分析,并且判别其内在逻辑和数据结构的相关性。通过建立二分类器,对乘客选择乘坐高铁还是火车进行分类和预测。

With the rapid development of railway technology in China,the mileage of high-speed railway has exceeded 20000 km,high-speed rail can reduce travel time and increase passenger comfort.As a result,more and more people choose high-speed rail travel.For college students,railway transportation is an indispensable way to go home during holidays,and more students choose to go home by high-speed rail.But because of various factors,there will still be students who choose to take the ordinary train home.Considering that the factors affecting students on high-speed rail and ordinary trains are more complex and have more research space,this paper will analyze and judge them correlation of intrinsic logic and data structure.Through the establishment of a two-classifier,passengers choose to take high-speed rail or train classification and prediction.