Hybrid forecasting model-based data mining and genetic algorithm-Adaptive particle swarm optimisation: A case study of wind speed time series

IET Renewable Power Generation

Volumn 10, Issue 3, 2016, Pages 287-298

  Wang, Jianzhou ^a   Zhang, Fanyong ^b   Liu, Feng ^a,b   Ma, Jianjun ^b  

^a DONGBEI UNIVERSITY OF FINANCE AND ECONOMICS   (China)

^b LANZHOU UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; BACKPROPAGATION; DATA MINING; FORECASTING; FUZZY NEURAL NETWORKS; GENETIC ALGORITHMS; PARTICLE SWARM OPTIMIZATION (PSO); RENEWABLE ENERGY RESOURCES; WIND; WIND POWER;

FORECASTING PERFORMANCE; METEOROLOGICAL FACTORS; PARTICLE SWARM OPTIMISATION; PARTICLE SWARM OPTIMISATION ALGORITHMS; RENEWABLE ENERGY SOURCE; WAVELET NEURAL NETWORKS; WIND SPEED FORECASTING; WIND SPEED TIME SERIES;

OPTIMIZATION;

EID: 84959359752     PISSN: 17521416     EISSN: 17521424     Source Type: Journal    
DOI: 10.1049/iet-rpg.2015.0010     Document Type: Article

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