EasyChair Preprint № 2672 Wind speed prediction using a hybrid model of the multi-layer perceptron and whale optimization algorithm Saeed Samadianfard, Sajjad Hashemi, Katayoun Kargar, Mojtaba Izadyar, Ali Mostafaeipour, Amir Mosavi, Narjes Nabipour and Shahaboddin Shamshirband EasyChair preprints are intended for rapid dissemination of research results and are integrated with the rest of EasyChair. February 15, 2020 Wind speed prediction using a hybrid model of the multi-layer perceptron and whale optimization algorithm Saeed Samadianfard 1, Sajjad Hashemi 1, Katayoun Kargar 2, Mojtaba Izadyar 1, Ali Mostafaeipour 3, Amir Mosavi 4*, Narjes Nabipour 5*, Shahaboddin Shamshirband 6,7* 1 Department of Water Engineering, Faculty of Agriculture, University of Tabriz, Tabriz, Iran,
[email protected] 2 Department of Civil Engineering, Faculty of Engineering, Urmia University, Urmia, Iran, 3 Industrial engineering Department, Yazd University, Yazd, Iran,
[email protected] 4 Kalman Kando Faculty of Electrical Engineering, Obuda University, 1034 Budapest, Hungary;
[email protected] 5 Institute of Research and Development, Duy Tan University, Da Nang 550000, Viet Nam Corresponding authors.
[email protected] 6 Department for Management of Science and Technology Development, Ton Duc Thang University, Ho Chi Minh City, Viet Nam;
[email protected], 7 Faculty of Information Technology, Ton Duc Thang University, Ho Chi Minh City, Viet Nam Abstract Wind power as a renewable source of energy, has several economic, environmental and social benefits. In order to enhance and control the renewable wind power, it is vital to utilize models that predict wind speed with high accuracy. Due to neglecting of requirement and significance of data preprocessing and disregarding the inadequacy of using a single predicting model, many traditional models have poor performance in wind speed prediction.