Using Fruit Fly Optimization Algorithm Optimized Grey Model Neural Network to Perform Satisfaction Analysis for E-Business Service

In recent years, the automation and electronic system in the logistics industr y have become popular topics in management, which consist of five segments, including marketing, logistics, information technology, banking system, and service system in the online stores (B2C & C2C) of the E-Commerce system. This study contains questionnaires and collective information that focus on logistics. In this article, the results of the survey questionnaires regarding the serv ice quality level of the e-business seller will be used first to conduct the Principal Components Analysis; then the FOA Optimized Grey Model Neural Network(FOAGMNN), the Grey Model Neural Network, and Multiple Regression will be further utilized to perform the construction of service satisfaction detection models. Based on the analysis results in this article, the FOAGMNN model has the fastest error convergence and the best classification forecast capability.