DocumentCode
501762
Title
Heat Load Forecasting Based on Improved AGA-BP Non-linear Combined Model
Author
Ren, Feng ; Liu, Ying-Zong ; Ding Chao
Author_Institution
Sch. of Bus. Adm., Tianjin Univ., Tianjin, China
Volume
1
fYear
2009
fDate
12-14 Aug. 2009
Firstpage
422
Lastpage
426
Abstract
A new combined BP neural network model based on accelerating genetic algorithm is put forward in this paper. On the foundation of traditional BP neural network, this method is given better iteration values improved by accelerating genetic algorithm, thus and increase iteration rate and avoid sinking into local minimum. Then, it is applied to forecast the heat load in a certain area, and compared with other forecasting methods. The calculation sample shows the exactitude and efficiency of this combined forecasting model.
Keywords
backpropagation; genetic algorithms; heat; load forecasting; neural nets; power engineering computing; AGA-BP nonlinear combined model; BP neural network; genetic algorithm; heat load forecasting; power forecasting; Acceleration; Artificial neural networks; Chaos; Cogeneration; Economic forecasting; Genetic algorithms; Load forecasting; Neural networks; Predictive models; Support vector machines; 1); AGA; BP; Combined Model; GM (1; Power Forecasting;
fLanguage
English
Publisher
ieee
Conference_Titel
Hybrid Intelligent Systems, 2009. HIS '09. Ninth International Conference on
Conference_Location
Shenyang
Print_ISBN
978-0-7695-3745-0
Type
conf
DOI
10.1109/HIS.2009.87
Filename
5254409
Link To Document