Solar Radiation Estimation in Mediterranean Climate by Weather Variables Using a Novel Bayesian Model Averaging and Mach
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Solar Radiation Estimation in Mediterranean Climate by Weather Variables Using a Novel Bayesian Model Averaging and Machine Learning Methods Ozgur Kisi1,2 · Meysam Alizamir2,3 · Slavisa Trajkovic4 · Jalal Shiri5 · Sungwon Kim6 Accepted: 5 September 2020 © Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract The present study investigated the potential of new ensemble method, Bayesian model averaging (BMA), in modeling monthly solar radiation based on climatic data. Data records covered monthly maximum temperature (Tmax ), minimum temperature (Tmin ), sunshine hours (Hs ), wind speed (Ws ), relative humidity (RH), and solar radiation values obtained from two weather stations of Turkey. The BMA estimates were compared with the artificial neural networks (ANN), extreme learning machines (ELM), radial basis function (RBF), and their hybrid versions with wavelet transform technique (wavelet-ANN or WANN, wavelet-ELM or WELM, and wavelet-RBF or WRBF). Three evaluation criteria e.g., root mean square error (RMSE), Nash–Sutcliffe efficiency, and determination coefficient (R2 ), were applied to measure the accuracy of the employed methods. The results indicated the superior accuracy of the BMA4 models over six machine learning models for estimating monthly solar radiation; improvements in accuracy of ANN4, ELM4, RBF4, WANN4, WELM4, and WRBF4 models comprising Tmax , Tmin , Hs , Ws and RH input variables were about 56–41%, 44–31%, 57–46%, 35–26%, 27–16%, and 43–28% in terms of RMSE reduction in both stations. While the hybrid models (i.e., WANN4, WELM4, and WRBF4) increased the accuracy of the single models about 31–21%, 23–18%, and 26–25% for ANN4, ELM4, and RBF4, respectively. Keywords Bayesian model averaging · Ensemble method · Solar radiation · Wavelet · Artificial neural networks · Extreme learning machines · Radial basis function
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Meysam Alizamir [email protected]
1
Civil Engineering Department, Ilia State University, Tbilisi, Georgia
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Institute of Research and Development, Duy Tan University, Da Nang 550000, Vietnam
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The Faculty of Civil Engineering, Duy Tan University, Da Nang 550000, Vietnam
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Faculty of Civil Engineering and Architecture, University of Nis, Aleksandra Medvedeva 14, Nish 18000, Serbia
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Water Engineering Department, Faculty of Agriculture, University of Tabriz, Tabriz, Iran
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Department of Railroad Construction and Safety Engineering, Dongyang University, Yeongju 36040, Republic of Korea
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O. Kisi et al.
1 Introduction Radiant energy emitted by the sun from a nuclear fusion reaction is called solar radiation [32]. This radiation is the main energy source and the engine that strengthens our environment obviously. An Information on solar radiation is important in many areas such as agriculture, meteorology, hydrology, architecture, and renewable solar energy systems. Solar energy is extensively studied worldwide, especially in solar-rich regions such as Mediterranean and Middle East [60]. Unfortunately, the observed solar radiation values are n
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