Electrical Energy Consumption Forecasting Based on Cointegration and a Support Vector Machine in China
نویسنده
چکیده
By undertaking a cointegration analysis with annual data over the period 1985~2005 in China, the estimation results show that there is cointegration relationship between electrical energy consumption and economic growth taking into account industry structure changes and technical efficiency. The model shows that three explanatory variables, the GDP per capita, heavy industry share and efficiency improvement are the crucial factors which influence the electric energy consumption. The three explanatory variables and the actual electrical energy consumption are input into a support vector machine(SVM), a Gaussian radial basis function is taken as the kernel function and electrical energy consumptions from 1994~2006 are forecasted. The forecast results prove that the multivariable SVM is valid in forecasting electrical energy consumption in China. Key-Words: Cointegration analysis; Electrical energy consumption; Johansen cointegration test; Multivariate time series; Support vector machine ; Unit root test
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