Applying rough set theory to establish artificial neural networks for short term load forecasting

Zhongguo Dianji Gongcheng Xuebao/Proceedings of the Chinese Society of Electrical Engineering

Volumn 23, Issue 11, 2003, Pages 1-4

  Xie, Hong ^a   Cheng, Hao Zhong ^a   Zhang, Guo Li ^b   Niu, Dong Xiao ^b   Yang, Jing Fei ^a  

^a SHANGHAI JIAO TONG UNIVERSITY   (China)

^b NORTH CHINA ELECTRIC POWER UNIVERSITY   (China)

Author keywords

Affecting factor; Load forecasting; Neural networks; Rough set

Indexed keywords

BACKPROPAGATION; DECISION TABLES; LEARNING ALGORITHMS; NEURAL NETWORKS; NONLINEAR SYSTEMS; OPTIMIZATION; ROUGH SET THEORY;

AFFECTING FACTOR;

ELECTRIC LOAD FORECASTING;

EID: 1542361556     PISSN: 02588013     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (5)

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2. Mastorococostas P A, Theocharis J B, Bakirtizis A G, Fuzzy modeling for short term load forecasting using the orthogonal least squares method[J]. IEEE Transaction on Power Systems, 1999, 14(1): 29-36.
3. Xie Hong, Chen Zhiye, Niu Dongxiao, et al. The research of daily load forecasting model based on wavelet decomposing and climate influencing[J]. Proceedings of the CSEE, 2001, 21(5): 5-10.
4. Wang Feng, Yu Erkang, Yan Chengshan, et al. Study of short term load forecasting based on influencing factors[J]. Proceedings of the CSEE, 1999, 19(8): 54-57.