Wind power prediction and pattern feature based on deep learning method

Asia-Pacific Power and Energy Engineering Conference, APPEEC

Volumn 2015-March, Issue March, 2014, Pages

  Tao, Yubo ^a   Chen, Hongkun ^a   Qiu, Chuang ^b  

^a WUHAN UNIVERSITY   (China)

^b Chongqing Electric Power Corporation   (China)

Author keywords

Boltzmann machine; deep belief network; neural network; pattern features; wind power prediction

Indexed keywords

ELECTRIC UTILITIES; FORECASTING; NEURAL NETWORKS; RENEWABLE ENERGY RESOURCES; WIND POWER;

ACCURATE PREDICTION; BOLTZMANN MACHINES; DEEP BELIEF NETWORK (DBN); DEEP BELIEF NETWORKS; PATTERN FEATURES; PREDICTION ERRORS; RENEWABLE ENERGY SOURCE; WIND POWER PREDICTIONS;

WEATHER FORECASTING;

EID: 84983098281     PISSN: 21574839     EISSN: 21574847     Source Type: Conference Proceeding    
DOI: 10.1109/APPEEC.2014.7066166     Document Type: Conference Paper

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