DocumentCode
3027899
Title
Electric power consumption forecast of life energy sources based on fuzzy neural network
Author
Xiufeng, Shao ; Jian, Zhang
Author_Institution
Dept. of Soft & Inf. Manage., BeiJing City Univ., Beijing, China
Volume
1
fYear
2011
fDate
9-11 Dec. 2011
Firstpage
309
Lastpage
312
Abstract
A fuzzy neural network(FNN) with five layers is proposed in this article. Aim at the structure optimization of network, a new node selection method and corresponding back propagation learning algorithm are presented. We use real history data to train the network model at the same time and to forecast the result after the train finished. Test results illustrate its good practicability to power consumption forecast of life energy sources.
Keywords
backpropagation; fuzzy neural nets; power consumption; power engineering computing; FNN; back propagation learning algorithm; electric power consumption forecast; fuzzy neural network; life energy sources; Data models; Economics; Fuzzy control; Fuzzy neural networks; Power systems; Predictive models; Vectors; electric power consumption forecast of life energy sources; fuzzy integrated judge; fuzzy neural network;
fLanguage
English
Publisher
ieee
Conference_Titel
IT in Medicine and Education (ITME), 2011 International Symposium on
Conference_Location
Cuangzhou
Print_ISBN
978-1-61284-701-6
Type
conf
DOI
10.1109/ITiME.2011.6130840
Filename
6130840
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