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

fYear

2009

fDate

11-13 Dec. 2009

Firstpage

1

Lastpage

4

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;

fLanguage

English

Publisher

ieee

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

Type

conf

DOI

10.1109/CISE.2009.5364394

Filename

5364394