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Spatial wind speed forecasting using artificial neural networks

Author(s)
Saif ur Rehman Department of Physics, Federal Urdu University of Arts, S&T,Karachi,Pakistan
Muhammad Shoaib Department of Physics, Federal Urdu University of Arts, S&T,Karachi,Pakistan
Imran Siddiqui Department of Physics, University of Karachi,Karachi-75270,Pakistan
Shamim Khan University Campus Peshawar,Khyber Pakhtunkhwa, 25120,Pakistan
Syed Zeeshan Abbas Department of Physics, University of Karachi,Karachi-75270,Pakistan
Abstract
Spatial interpolation is a commonly used technique to simulate wind speeds in areas which are devoid of such measuring devices. In this paper authors examine the applicability and efficiency of Artificial-Neural- Network (ANN) formalism aimed at interpolating wind speeds in space domain. Additionally, the effect of the correlation between the wind speed at target site and its correlated neighboring site is also examined in the present paper. Hourly wind speed data set comprising of wind speeds recorded from April 2016 to August 2018 provided by Energy Sector Management Assistance Program of World Bank is used for the study. The study is supported by including four different wind speed measuring stations in Pakistan, namely, Tando Ghulam Ali, Umer Kot, Sujawal and Sanghar. Best estimates from ANN model are obtained for Tando Ghulam Ali (MAPE= 7.37%) and worst estimates are observed for Sanghar site (MAPE= 10.61%).
Publication Details
Page(s) 37-42
DOI DOI not available
Published Journal: International Journal of Economic and Environmental Geology, Volume: 11, Issue: 4, Year: 2020

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Keywords
Artificial Neural Network, wind speed, Prediction, Spatial Interpolation, target station
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