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Energy Sources, Part A: Recovery, Utilization, and Environmental Effects Volume 34, 2012 - Issue 14
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Original Articles

Splitting Global Solar Radiation into Diffuse and Direct Normal Fractions Using Artificial Neural Networks

S. Rehman Engineering Analysis Section, Center for Engineering Research, Research Institute, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia
&
M. Mohandes Electrical Engineering Department, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia
Pages 1326-1336 | Received 06 Feb 2010, Accepted 19 Mar 2010, Published online: 31 May 2012

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Abdelaziz Rabehi, Mawloud Guermoui, Reski Khelifi & Mohamed Lamine Mekhalfi. (2020) Decomposing global solar radiation into its diffuse and direct normal radiation. International Journal of Ambient Energy 41:7, pages 738-743.
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T. R. Ayodele & A. S. O. Ogunjuyigbe. (2017) Performance assessment of empirical models for prediction of daily and monthly average global solar radiation: the case study of Ibadan, Nigeria. International Journal of Ambient Energy 38:8, pages 803-813.
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K. Kaba, H. M. Kandirmaz & M. Avci. (2017) Estimation of daily sunshine duration using support vector machines. International Journal of Green Energy 14:4, pages 430-441.
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Jamil M. Bakhashwain. (2016) Prediction of global solar radiation using support vector machines. International Journal of Green Energy 13:14, pages 1467-1472.
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Articles from other publishers (15)

Shubham Gupta, Amit Kumar Singh, Sachin Mishra, Pradeep Vishnuram, Nagaraju Dharavat, Narayanamoorthi Rajamanickam, Ch. Naga Sai Kalyan, Kareem M. AboRas, Naveen Kumar Sharma & Mohit Bajaj. (2023) Estimation of Solar Radiation with Consideration of Terrestrial Losses at a Selected Location—A Review. Sustainability 15:13, pages 9962.
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Hailong Huang, Shahab S. Band, Hojat Karami, Mohammad Ehteram, Kwok-wing Chau & Qian Zhang. (2022) Solar radiation prediction using improved soft computing models for semi-arid, slightly-arid and humid climates. Alexandria Engineering Journal 61:12, pages 10631-10657.
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Anand Mohan & Gopal Singh. 2022. Renewable Energy Systems. Renewable Energy Systems 403 452 .
Pravat Kumar Ray, Anindya Bharatee, Pratap Sekhar Puhan & Sourav Sahoo. (2022) Solar Irradiance Forecasting Using an Artificial Intelligence Model. Solar Irradiance Forecasting Using an Artificial Intelligence Model.
A.D. Dhass & Dhiren PatelR.R.. (2022) Thermodynamic analysis of reflected solar radiation on tilted PV module in south India. FME Transactions 50:2, pages 158-167.
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Amar Choudhary, Deependra Pandey & Saurabh Bhardwaj. 2021. Intelligent and Cloud Computing. Intelligent and Cloud Computing 59 66 .
Yaser I. Alamin, Mensah K. Anaty, José Domingo Álvarez Hervás, Khalid Bouziane, Manuel Pérez García, Reda Yaagoubi, María del Mar Castilla, Merouan Belkasmi & Mohammed Aggour. (2020) Very Short-Term Power Forecasting of High Concentrator Photovoltaic Power Facility by Implementing Artificial Neural Network. Energies 13:13, pages 3493.
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Mawloud Guermoui, Farid Melgani & Céline Danilo. (2018) Multi-step ahead forecasting of daily global and direct solar radiation: A review and case study of Ghardaia region. Journal of Cleaner Production 201, pages 716-734.
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Florencia Almonacid, Eduardo F. Fernandez, Adel Mellit & Soteris Kalogirou. (2017) Review of techniques based on artificial neural networks for the electrical characterization of concentrator photovoltaic technology. Renewable and Sustainable Energy Reviews 75, pages 938-953.
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Basharat Jamil & Abid T. Siddiqui. (2017) Generalized models for estimation of diffuse solar radiation based on clearness index and sunshine duration in India: Applicability under different climatic zones. Journal of Atmospheric and Solar-Terrestrial Physics 157-158, pages 16-34.
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R. Tapakis, S. Michaelides & A.G. Charalambides. (2016) Computations of diffuse fraction of global irradiance: Part 2 – Neural Networks. Solar Energy 139, pages 723-732.
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Sthitapragyan Mohanty, Prashanta Kumar Patra & Sudhansu Sekhar Sahoo. (2016) Prediction and application of solar radiation with soft computing over traditional and conventional approach – A comprehensive review. Renewable and Sustainable Energy Reviews 56, pages 778-796.
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Rajesh Kumar, R.K. Aggarwal & J.D. Sharma. (2015) Comparison of regression and artificial neural network models for estimation of global solar radiations. Renewable and Sustainable Energy Reviews 52, pages 1294-1299.
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Florencia Almonacid, Adel Mellit & Soteris A. Kalogirou. 2015. High Concentrator Photovoltaics. High Concentrator Photovoltaics 333 351 .
Amit Kumar Yadav & S.S. Chandel. (2014) Solar radiation prediction using Artificial Neural Network techniques: A review. Renewable and Sustainable Energy Reviews 33, pages 772-781.
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