Seasonal load forecast methods based on grey Support Vector Machine

Because of the dual trends(increase and fluctuation) and their complex nonlinearity,the seasonal load which is also subject to multiple stochastic interference factors is difficult to be forecasted with single model.To solve the problem,a forecast system using rough set-based grey Support Vector Machine is proposed and was applied to seasonal load forecast.The system is accurate in forecast in comparison with the single GM(1,1) method and BP neural network method.