基于粗糙集与BP神经网络相融合的第三方物流企业客户满意度评价研究  

Study on Evaluation of Third Party Logistics Enterprise Customer Satisfaction Based on Rough Set and BP Neural Network

作　　者：邵为爽[1] 李晓红[1] 

机构地区：[1]齐齐哈尔大学理学院,黑龙江齐齐哈尔161006

出　　处：《物流技术》2013年第7期257-259,359,共4页Logistics Technology

基　　金：黑龙江省自然科学基金(A201014);齐齐哈尔大学青年教师科研启动项目(2012K-M27)

摘　　要：将粗糙集理论与BP神经网络在处理多因素及非线性方面的优势融合,建立了第三方物流企业客户满意度评价模型,应用Matlab软件训练并对认定结果进行仿真,分析结果表明经粗糙集属性约简后再与BP网络相结合的模型,在训练次数、速度和识别率上都有所提高,用于第三方物流企业客户满意度评价行之有效。In this paper, by combining the rough set theory with the advantage of the BP neural network in solving multi-factor and non-linear problems, we established the model for evaluating the customer satisfaction of third party logistics enterprises, applied the Matlab program to train it and simulate the result obtained, and at the end found that the model obtained after reducing the attribute of the rough set and then integrating it with the BP network was superior in training times, speed and detection rate.

关 键 词：粗糙集 属性约简 第三方物流企业 客户满意度 BP神经网络 

分 类 号：F224[经济管理—国民经济] F253