NDLI: Modeling and Forecasting of High-Technology Manufacturing Labor Productivity Based on Grey Support Vector Machines with Genetic Algorithms

Content Provider	IEEE Xplore Digital Library
Author	Sheng Xu Hui-Fang Zhao Jie Liu Xiang Sun
Copyright Year	2006
Description	Author affiliation: Sch. of Manage., Hefei Univ. of Technol. (Sheng Xu; Hui-Fang Zhao)
Abstract	In recent years, computing high-technology manufacturing (HTM) labor productivity (LP) level and growth rate has gained a renewed interest in both growth economists and trade economists. Measuring LP performance has become an area of concern for companies and policy makers. HTM LP is complex to conduct due to its nonlinearity of influenced factors. Support vector machines (SVM) have been successfully employed to solve nonlinear regression and time series problems. Grey system theory successfully utilizes accumulated generating data instead of original data to build forecasting model, which makes raw data stochastic weak, or reduces noise influence in a certain extent. However, the application combining grey system theory and SVM for LP forecasting is rare. In this study, a grey support vector machines with genetic algorithms (GSVMG) is proposed to forecast HTM LP. In addition, GM (1, N) model of grey system is used to add a grey layer before neural input layer and white layer after SVM layer. Genetic algorithms (GAs) are used to determine free parameters of support vector machines. Evaluation method has been used for comparing the performance of forecasting techniques. The experiments show that the GSVMG model is outperformed GM (1, N) model and SVM with genetic algorithms (SVMG) model, and HTM LP forecasting based on GSVMG is of validity and feasibility
Sponsorship	IEEE Syst., Man and Cybernetics Hebei Univ.
Starting Page	2419
Ending Page	2424
File Size	276142
Page Count	6
File Format	PDF
ISBN	1424400619
DOI	10.1109/ICMLC.2006.258772
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-08-13
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Predictive models Virtual manufacturing Productivity Support vector machines Genetic algorithms Economic forecasting Computer aided manufacturing Area measurement Stochastic systems Stochastic resonance genetic algorithms High-technology manufacturing labor productivity support vector machines GM (1 N)
Content Type	Text
Resource Type	Article

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