DocumentCode :
3227973
Title :
A new modeling method based on bagging ELM for day-ahead electricity price prediction
Author :
Tian, Huixin ; Meng, Bo
Author_Institution :
First-Third Dept., First-Third Univ., Tianjin, China
fYear :
2010
fDate :
23-26 Sept. 2010
Firstpage :
1076
Lastpage :
1079
Abstract :
Aiming at the shortages of traditional neural networks, a new modeling method based on Bagging ELM is proposed to establish the electricity price prediction model. The characters of day-ahead electricity price are analyzed and a novel neural network algorithm ELM is selected for its better performance to establish the basic day-ahead electricity price prediction model. Motivated by the ensemble ideas, a Bagging ensemble scheme is used to combining the single ELM learning machines. And the new Bagging ELM modeling approach is used to establish the prediction model. The day-ahead electricity price prediction model is tested by the real data. The experiments demonstrate that the new prediction model established by the new Bagging ELM modelling method has better performance.
Keywords :
learning (artificial intelligence); neural nets; power engineering computing; power markets; pricing; bagging ELM; bagging ensemble scheme; day-ahead electricity price prediction; extreme learning machine; modeling method; neural network algorithm; Manuals; Predictive models; Bagging; ELM; electricity price prediction; modeling method;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Bio-Inspired Computing: Theories and Applications (BIC-TA), 2010 IEEE Fifth International Conference on
Conference_Location :
Changsha
Print_ISBN :
978-1-4244-6437-1
Type :
conf
DOI :
10.1109/BICTA.2010.5645111
Filename :
5645111
Link To Document :
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