Abstract: In the process of cointegration analysis, electricity consumption is chosen as the explained variable, and GDP per capita, heavy industry share, and efficiency improvement are chosen as the explanatory variables; then a cointegration model is put forward, which shows that there is a cointegration relationship between the explained variable and explanatory variables. The explained and explanatory variables are input into a support vector machine (SVM), and a Gaussian radial basis function is taken as the kernel function. So an electricity demand forecasting model based on multivariate SVM is established. The example provides evidence for the validity of the forecasting model
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