Solar Energy Forecasting Using Fuzzy Logic and Artificial Neural Network
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-19-0244-4_47
Reference14 articles.
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3. Alfredo Fernandez-Jimenez L, Muñoz-Jimenez A, Falces A, Mendoza-Villena M, Garcia-Garrido E, Lara-Santillan PM, Zorzano-Alba E, Zorzano-Santamaria PJ (2012) Short-term power forecasting system for photovoltaic plants. Renew Energy 44:311–317, ISSN 0960-1481. https://doi.org/10.1016/j.renene.2012.01.108
4. Ncane ZP, Saha AK (2019) Forecasting solar power generation using fuzzy logic and artificial neural network. 2019 Southern African universities power engineering conference/robotics and mechatronics/pattern recognition association of South Africa (SAUPEC/RobMech/PRASA), Bloemfontein, South Africa, 2019, pp. 518–523. https://doi.org/10.1109/RoboMech.2019.8704737
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