基于Adam神经网络的顾客满意度预测与应用

Customer Satisfaction Prediction and Application Based on Adam Neural Network

针对传统方法难以满足当前环境下顾客满意度预测要求的问题,考虑顾客满意度建立质量成本3级科目,提出了一种基于Adam神经网络的顾客满意度预测模型,以弥补经典神经网络预测方法性能不稳定的缺陷。为验证模型有效性,对某建材装备制造企业实例进行实验分析,并与其他现有算法进行对比。结果证明,该预测模型在建材装备制造企业考虑质量成本指标下对顾客满意度预测可行性强、准确性高。

Under the environment of customer satisfaction oriented market economy,higher requirements for product quality cost control and customer satisfaction evaluation are put forward,which makes traditional methods difficult to meet the needs of customer satisfaction prediction in the current environment. In this paper,a quality cost three level account is established considering customer satisfaction. A prediction model of customer satisfaction based on Adam neural network is proposed to compensate for the unstable performance of classical neural network. In order to validate this model,an example of the building materials manufacturing enterprises evaluation was carried out and compared with other existing algorithms. The results show that the prediction model developed in this work has high feasibility and accuracy for predicting customer satisfaction under the consideration of quality cost index in manufacturing enterprisesof building material equipment.