A P-SVM and chaos based model for high-technology manufacturing labor productivity

Computing high-technology manufacturing (HTM) productivity level and growth rate have gained a renewed interest in both growth economists and trade economists. Measuring productivity performance has become an area of concern for companies and policy makers. A novel way about nonlinear regression modeling of high-technology manufacturing (HTM) productivity with the potential support vector machines (P-SVM) is presented in this paper. Optimization of labor productivity (LP) is also presented in this paper, which is based on chaos and uses the P-SVM regression model as the objective function.