Modeling and optimization of high-technology manufacturing productivity based on PCA SVM and chaos

作者：Xu Sheng; Zhao Huifang; Yan Dun; Bao Xiaohua

来源：Dynamics of Continuous Discrete and Impulsive Systems: Series B; Applications and Algorithms , 2006, 13: 605-609.

In this study, an alternative method was presented intended for analysis of high-technology manufacturing (HTM) productivity. The aim of in this study was to modeling the HTM labor productivity (LP), find out the main affecting factors and optimize the results of HTM LP growth. In recent years, measuring productivity performance has become an area of concern for companies and policy makers. A novel way about nonlinear regression modeling of HTM productivity with the support vector machines (SVM) combining principal component analysis (PCA) is presented in this paper. Optimization of LP and the main factors of affecting HTM LP growth are also presented in this paper, which is based on chaos and uses the PCA SVM regression model as the objective function.

• 出版日期2006-12
• 单位合肥工业大学; 西安交通大学