Solar Energy Prediction Model Based on Artificial Neural Networks and Open Data
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- Panagiotis Korkidis & Anastasios Dounis, 2023. "Intelligent Fuzzy Models: WM, ANFIS, and Patch Learning for the Competitive Forecasting of Environmental Variables," Sustainability, MDPI, vol. 15(10), pages 1-21, May.
- Guangying Jin & Wei Feng & Qingpu Meng, 2022. "Prediction of Waterway Cargo Transportation Volume to Support Maritime Transportation Systems Based on GA-BP Neural Network Optimization," Sustainability, MDPI, vol. 14(21), pages 1-24, October.
- Sojung Kim & Sumin Kim, 2021. "Performance Estimation Modeling via Machine Learning of an Agrophotovoltaic System in South Korea," Energies, MDPI, vol. 14(20), pages 1-13, October.
- Sheik Mohammed S. & Femin Titus & Sudhakar Babu Thanikanti & Sulaiman S. M. & Sanchari Deb & Nallapaneni Manoj Kumar, 2022. "Charge Scheduling Optimization of Plug-In Electric Vehicle in a PV Powered Grid-Connected Charging Station Based on Day-Ahead Solar Energy Forecasting in Australia," Sustainability, MDPI, vol. 14(6), pages 1-20, March.
- Natei Ermias Benti & Mesfin Diro Chaka & Addisu Gezahegn Semie, 2023. "Forecasting Renewable Energy Generation with Machine Learning and Deep Learning: Current Advances and Future Prospects," Sustainability, MDPI, vol. 15(9), pages 1-33, April.
- Vladimir Franki & Darin Majnarić & Alfredo Višković, 2023. "A Comprehensive Review of Artificial Intelligence (AI) Companies in the Power Sector," Energies, MDPI, vol. 16(3), pages 1-35, January.
- Hossein Moayedi & Amir Mosavi, 2021. "An Innovative Metaheuristic Strategy for Solar Energy Management through a Neural Networks Framework," Energies, MDPI, vol. 14(4), pages 1-18, February.
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Keywords
solar energy; prediction; forecasting; open data; artificial neural networks; deep learning; IoT; artificial intelligence;All these keywords.
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