基于神经网络的汽车维修企业顾客满意度测评

Study on Customer Satisfaction Degree of Automobile Repairing Enterprise Based on Neural Network

为了更好地研究汽车维修企业的顾客满意度测评方法,对神经网络模型进行了分析,并以汽车维修企业顾客满意度调研数据为基础,利用BP和ELMAN神经网络对16组样本数据进行了网络训练,对4组样本数据进行了预测,结果表明将神经网络应用于汽车维修企业顾客满意度测评是可行的,且ELMAN网络性能明显优于BP神经网络。

In order to research the assessment method of automobile repairing enterprise＇s customer satisfaction degree,the neural network model is analyzed.Sixteen groups sample data are used for training,and four groups sample data are used for forecasting by using BP and ELMAN neural network theory based on investigation data.The results indicate that neural network theory is applicable in customer satisfaction measurement of automobile repairing enterprise,and ELMAN network＇s performance is better than BP＇s.