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基于支持向量机的物流服务顾客满意度评价模型
引用本文:孙华丽,谢剑英,薛耀锋.基于支持向量机的物流服务顾客满意度评价模型[J].上海交通大学学报,2006,40(4):684-688.
作者姓名:孙华丽  谢剑英  薛耀锋
作者单位:上海交通大学,自动化系,上海,200240
摘    要:提出了一种新的基于支持向量机(SVM)的物流服务顾客满意度(CSD)评价方法.归纳了物流服务CSD指标体系的设计原则,给出了具体的评价指标体系并采用模糊隶属函数和二元对比排序法对其进行量化.将量化后的指标因素集作为SVM的训练集,采用一对一的分类策略建立了CSD的评价模型.最后通过仿真实验指出了基于SVM的CSD评价方法比以往的模糊综合评价法和神经网络评价法测试正确率高,实用性强.

关 键 词:物流  评价模型  模糊隶属函数  二元对比排序法  支持向量机  顾客满意度
文章编号:1006-2467(2006)04-0684-05
收稿时间:2005-03-30
修稿时间:2005年3月30日

A Customer Satisfaction Degree Evaluation Model Based on SVM in Logistics
SUN Hua-li,XIE Jian-ying,XUE Yao-feng.A Customer Satisfaction Degree Evaluation Model Based on SVM in Logistics[J].Journal of Shanghai Jiaotong University,2006,40(4):684-688.
Authors:SUN Hua-li  XIE Jian-ying  XUE Yao-feng
Institution:Dept. of Automation, Shanghai Jiaotong Univ. , Shanghai 200240, China
Abstract:A novel evaluation method of customer satisfaction degree(CSD) in logistics based on support vector machine(SVM) was presented.The rules of designing key indexes were discussed and the evaluation index system was given.Fuzzy membership function and pairwise comparison were used to quantify the indices.Then the CSD evaluation system based on one-against-one mode of SVM was built. Lastly,simulation was given to support the theoretical result.
Keywords:logistics  evaluation model  fuzzy membership function  pairwise comparison  support vector machine(SVM)  customer satisfaction degree(CSD)  
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