DocumentCode :
3517579
Title :
Power load forecasting based on elman neural network
Author :
Heng, Zhang ; Huanqi, Tao
Author_Institution :
Coll. of Electron. & Inf. Eng., Wuhan Univ. of Sci. & Eng., Wuhan, China
Volume :
4
fYear :
2009
fDate :
8-9 Aug. 2009
Firstpage :
374
Lastpage :
376
Abstract :
The article forecasts the power load with Elman neural network. First of all, it gives the basic principle of Elman neural network, and then it determines the structure parameters, transfer function and training times of model, normalizes the data. It gets a good result with forecasting actual history data of a certain electric network; it shows that forecasting power load with Elman neural network is available.
Keywords :
load forecasting; neural nets; power engineering computing; transfer functions; Elman neural network; power load forecasting; transfer function; Economic forecasting; Educational institutions; Load forecasting; Neural networks; Neurons; Nonlinear dynamical systems; Power engineering and energy; Power generation economics; Recurrent neural networks; Transfer functions; Elman neural network; forecast; forecast accuracy; normalization; power load;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computing, Communication, Control, and Management, 2009. CCCM 2009. ISECS International Colloquium on
Conference_Location :
Sanya
Print_ISBN :
978-1-4244-4247-8
Type :
conf
DOI :
10.1109/CCCM.2009.5270429
Filename :
5270429
Link To Document :
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