关键词: 改进灰色关联分析模型-逼近理想解排序法, 网络服务质量, 稀疏自编码网络

Abstract: With the rapid development of modern society and economy,computer network has been widely used in all walks of life,and plays an irreplaceable important role.At the same time,we also puts forward more specific requirements for computer network service quality.How to realize network service quality assurance has always been a hot research topic in the Internet field.This paper analyzes the defects of the current comprehensive evaluation research on network service quality,and at the same time,considers that the shortcomings of traditional data processing methods will be magnified infinitely in the face of huge data volume and various data types.The sparse auto encoder network model is used to conduct data reduction and feature extraction for multidimensional data.Then,the feature data set is taken as experimental data,and the improved grey relational analysis-technique for order preference by similarity to ideal solution model is used to conduct comprehensive evaluation on network service quality.It provides a new way of thinking for multilevel and multicriteria comprehensive evaluation system.

Key words: Improved GRA-TOPSIS, Network quality of service, Sparse auto encoder network