Modeling of global horizontal irradiance in the United Arab Emirates with artificial neural networks
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DOI: 10.1016/j.energy.2014.09.064
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Cited by:
- Liu, Guanjun & Qin, Hui & Shen, Qin & Lyv, Hao & Qu, Yuhua & Fu, Jialong & Liu, Yongqi & Zhou, Jianzhong, 2021. "Probabilistic spatiotemporal solar irradiation forecasting using deep ensembles convolutional shared weight long short-term memory network," Applied Energy, Elsevier, vol. 300(C).
- Han, Yongming & Fan, Chenyu & Geng, Zhiqiang & Ma, Bo & Cong, Di & Chen, Kai & Yu, Bin, 2020. "Energy efficient building envelope using novel RBF neural network integrated affinity propagation," Energy, Elsevier, vol. 209(C).
- Aydin Jadidi & Raimundo Menezes & Nilmar De Souza & Antonio Cezar De Castro Lima, 2018. "A Hybrid GA–MLPNN Model for One-Hour-Ahead Forecasting of the Global Horizontal Irradiance in Elizabeth City, North Carolina," Energies, MDPI, vol. 11(10), pages 1-18, October.
- Koussa, Mustapha & Saheb-Koussa, Djohra & Hadji, Seddik, 2017. "Experimental investigation of simple solar radiation spectral model performances under a Mediterranean Algerian's climate," Energy, Elsevier, vol. 120(C), pages 751-773.
- Ayodele, T.R. & Ogunjuyigbe, A.S.O., 2015. "Prediction of monthly average global solar radiation based on statistical distribution of clearness index," Energy, Elsevier, vol. 90(P2), pages 1733-1742.
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Keywords
Global horizontal irradiance; Artificial neural network; Multilayer perceptron; Radial basis function; Estimation; United Arab Emirates;All these keywords.
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