Short-term electricity price prediction based on resilient adaptive artificial fish school algorithm and back propagation neural network hybrid algorithm

Shuili Fadian Xuebao/Journal of Hydroelectric Engineering

Volumn 29, Issue 1, 2010, Pages 106-113

  Shi, Biao ^a   Li, Yuxia ^a   Yu, Xinhua ^b   Yan, Wang ^a   Li, Na ^a   Meng, Xin ^a   Li, Peng ^a  

^a XI'AN UNIVERSITY OF TECHNOLOGY   (China)

^b QINGDAO UNIVERSITY OF SCIENCE AND TECHNOLOGY   (China)

Author keywords

RAAFSH BP hybrid algorithm; Resilient adaptive artificial fish school algorithm; Short term price forecast; The back propagation neural network

Indexed keywords

ARTIFICIAL FISH SCHOOL ALGORITHM; BACK PROPAGATION NEURAL NETWORKS; BP NEURAL NETWORKS; ELECTRICITY PRICES; FASTER CONVERGENCE; FORECAST MODEL; HYBRID ALGORITHMS; MAXIMUM ERROR; MEAN RELATIVE ERROR; MODEL PARAMETERS; POWER MARKETS; PRICE FORECASTS; SAMPLE DATA; TEST RESULTS;

ADAPTIVE ALGORITHMS; BACKPROPAGATION; COSTS; DATA FLOW ANALYSIS; ELECTRIC LOAD FORECASTING; FISH; MEATS; STATISTICAL TESTS;

NEURAL NETWORKS;

EID: 77950549475     PISSN: 10031243     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

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