关键词: 生产线, 健康度, 层次分析法, 物元信息熵, 支持向量机

Abstract: To evaluate and predict the health index of product line,the physical element information entropy and Support Vector Machine (SVM) were proposed.The interchange complex matter element which composed of running state,energy consumption,production rate and production efficiency was designed.The theoretical weights were determined with Analytic Hierarchy Process (AHP),the objective weights were determined with entropy method,and the joint weights were combined theoretical weights and objective weights.The health index of production line was calculated by using the compound matter element correlation entropy.SVM was optimized by grid search,genetic algorithm and Particle Swam Optimization (PSO) to predict the health index.The result shows that SVM based on PSO had prominent prediction effect on the health index.It provided data support and theoretical basis for the production of Beer filling production line.

Key words: production line, health index, analytic hierarchy process, matter element information entropy, support vector machine