路面质量影响因素分析——支持向量机模型  

An Analysis of the Highway Ground Quality Using SVMs

作　　者：陶甄[1] 吴元[2] 梁晓辉[2] 

机构地区：[1]上海交通大学金融系,上海200030 [2]上海交通大学计算机科学与工程系,上海200240

出　　处：《数学的实践与认识》2008年第14期160-163,共4页Mathematics in Practice and Theory

摘　　要：支持向量机(Support Vector Machines)是近年来热门的一种有监督学习的方法,它广泛的应用于统计分类以及回归分析中.通过SVM模型,考察分析一系列影响因素对高速公路路面质量指标的影响,并对提高高速公路路面质量提出建议.Support vector machines （SVMs） are a set of related supervised learning methods used for classification and regression, which is quite hot these years. In this paper, we observed and analyzed the factors that were supposed to have impact on the highway ground quality by using SVMs. And we reached several conclusion about the improvement of the highway ground quality.

关 键 词：支持向量机 路面质量 高速公路 质量管理 

分 类 号：U416.2[交通运输工程—道路与铁道工程] O242.1[理学—计算数学]