WSFNet: An efficient wind speed forecasting model using channel attention-based densely connected convolutional neural network
Date
2021Author
Acikgoz, Hakan
Budak, Umit
Korkmaz, Deniz
Yildiz, Ceyhun
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This paper introduces a novel deep neural network (WSFNet) to efficiently forecast multi-step ahead wind speed. WSFNet forms the basis of the stacked convolutional neural network (CNN) with dense connections of different blocks equipped with the channel a
URI
http://dspace.beu.edu.tr:8080/xmlui/handle/20.500.12643/9809https://doi.org/10.1016/j.energy.2021.121121
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