一种基于BP神经网络的B2C电子商务顾客满意度评价模型

Evaluation Model of Customer Satisfaction in B2C Electronic Commerce based on BP Neural Network

针对当前电子商务顾客满意度评价方法所存在的不足,提出一种基于BP神经网络的评价模型。首先,建立了B2C模式下电子商务企业顾客满意度评价指标体系,然后根据指标体系,设计了BP神经网络模型,并利用神经网络工具箱对模型进行了实现,通过学习样本的训练,使模型的误差达到预定的范围内.验证结果表明,BP神经网络方法对B2C模式下电子商务企业顾客满意度评价有着良好的效果。

Because of the defects of the current method of evaluation of customer satisfaction in B2C electronic commerce enterprise, the paper presents a new method of evaluation of customer satisfaction, which is based on BP neural network. Firstly, it sets up an index system to evaluate customer satisfaction, and designs the BP neural network model according the index system, the Neural Network Toolbox （NNT） based on MAT-LAB is used to build up network. Through the training and test of lots of study samples, the error of the model is limited to a preliminary range. The rationality of experiment results indicates that BP neural network can evaluate customer satisfaction in B2C electronic commerce enterprise accurately and efficiently.