Research On Optimization Method For Knowledge Service Composition In Cloud Manufacturing Environment Based On User's Psychological Behavior

Cloud manufacturing mode provides a new approach for Chinese manufacturing enterprises to improve their independent innovation ability and comprehensive competitiveness.As an important component of cloud manufacturing services,the quality of service for knowledge service is one of the keys for enterprises applying cloud manufacturing to gain or maintain competitiveness.With the diversification and increasing complexity of users'needs,single-function knowledge service can no longer meet the actual needs provided by users.Compositing the most suitable knowledge services to provide users with high-quality and efficient knowledge services has become one of the most critical issues in cloud manufacturing.Therefore,based on existing research results,this paper makes a certain exploration and study on a knowledge service composition optimization method in cloud manufacturing environment based on user's psychological behavior.Firstly,characteristics,existing problems and requirements of knowledge service composition in cloud manufacturing environment are analyzed.Based on the analysis,an implementation framework for knowledge service composition optimization in cloud manufacturing environment based on user's psychological behavior is established.Secondly,based on the analysis of the whole life cycle process of knowledge service in cloud manufacturing environment,a decision-making index system of knowledge service composition optimization in cloud manufacturing environment is constructed,including eight-dimensional variables-service time ₁I,composability I₂,service practicability I₃,service relevance I₄,service cost I₅,sustainability I₆,credibility I₇ and comprehensive satisfaction I₈.Combined with the psychological behavior analysis of users'and the regret theory in the decision-making process,a decision-making model of knowledge service composition optimization in cloud manufacturing environment is established.Then,based on rough-set theory,user's multi-attribute preference and improved particle swarm optimization algorithm,the optimization decision-making model of knowledge service composition in cloud manufacturing environment is solved to obtain the optimal composition strategy of knowledge service.Finally,based on the above research results,a set of optimization support system for cloud manufacturing knowledge service composition is designed and developed.The effectiveness of the above research production is preliminarily verified,and some application results are achieved.