A novel Grouping Genetic Algorithm–Extreme Learning Machine approach for global solar radiation prediction from numerical weather models inputs

Author:

Aybar-Ruiz A.,Jiménez-Fernández S.,Cornejo-Bueno L.,Casanova-Mateo C.,Sanz-Justo J.,Salvador-González P.,Salcedo-Sanz S.

Funder

Spanish Ministerial Commission of Science and Technology

Comunidad Autónoma de Madrid

Publisher

Elsevier BV

Subject

General Materials Science,Renewable Energy, Sustainability and the Environment

Reference56 articles.

1. Near optimal citywide WiFi network deployment using a hybrid grouping genetic algorithm;Agustín-Blas;Expert Syst. Appl.,2011

2. Alharbi, M.A., 2013. Daily Global Solar Radiation Forecasting using ANN and Extreme Learning Machines: A Case Study in Saudi Arabia (Master of Applied Science Thesis). Dalhousie University, Halifax, Nova Scotia.

3. The potential of different artificial neural network (ANN) techniques in daily global solar radiation modeling based on meteorological data;Behrang;Sol. Energy,2010

4. Radial basis function network-based prediction of global solar radiation data: application for sizing of a stand-alone photovoltaic system at Al-Madinah, Saudi Arabia;Benghanem;Energy,2010

5. Beyer, H.G., Polo Martinez, J., Suri, M., et al., 2011. Deliverable 1.1.3. Report on Benchmarking of Radiation Products. Report under contract no. 038665 of MESoR. .

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