Title :
Energy Forecast Model Based on Combination of GM(1,1) and Neural Network
Author :
Liu, Ren-yuan ; Zhang, Jue ; Huang, Qiang ; Lei, Bao-dong
Author_Institution :
Dept. of Water Resources, Shenzhen Water Eng. Constr. Manage. Center, Shenzhen, China
Abstract :
Energy consumption forecast is an essential component in making energy plan. In the light of the complexity and nonlinearity of energy consumption system, the gray forecast model and neural network model are respectively established by using the energy consumption historical data of certain province. Then their advantages and disadvantages are analyzed. Lastly, the method of optimal combination is applied in this paper in order to obtain accurate forecast model and forecast value. The forecast results of example show that the model can be regarded as effective tool of energy consumption forecast.
Keywords :
energy consumption; forecasting theory; neural nets; energy consumption forecast; energy consumption historical data; energy forecast model; gray forecast model; neural network; optimal combination; Artificial neural networks; Demand forecasting; Design engineering; Differential equations; Energy consumption; Load forecasting; Neural networks; Power engineering and energy; Predictive models; Water resources;
Conference_Titel :
Computational Intelligence and Software Engineering, 2009. CiSE 2009. International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-4507-3
Electronic_ISBN :
978-1-4244-4507-3
DOI :
10.1109/CISE.2009.5364394
