Neural Networks in the Diagnostics Process of Low-Power Solar Plant Devices
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- WenBo Xiao & Gina Nazario & HuaMing Wu & HuaMing Zhang & Feng Cheng, 2017. "A neural network based computational model to predict the output power of different types of photovoltaic cells," PLOS ONE, Public Library of Science, vol. 12(9), pages 1-8, September.
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Cited by:
- Zheng Xu, 2022. "Three Technical Challenges Faced by Power Systems in Transition," Energies, MDPI, vol. 15(12), pages 1-21, June.
- Marcin Kaminski & Tomasz Tarczewski, 2023. "Neural Network Applications in Electrical Drives—Trends in Control, Estimation, Diagnostics, and Construction," Energies, MDPI, vol. 16(11), pages 1-25, May.
- Jacek Paś, 2023. "Issues Related to Power Supply Reliability in Integrated Electronic Security Systems Operated in Buildings and Vast Areas," Energies, MDPI, vol. 16(8), pages 1-22, April.
- Dorian Skrobek & Jaroslaw Krzywanski & Marcin Sosnowski & Ghulam Moeen Uddin & Waqar Muhammad Ashraf & Karolina Grabowska & Anna Zylka & Anna Kulakowska & Wojciech Nowak, 2023. "Artificial Intelligence for Energy Processes and Systems: Applications and Perspectives," Energies, MDPI, vol. 16(8), pages 1-12, April.
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Keywords
neural networks; intelligent systems; servicing process; diagnostic process; expert system; knowledge base; low-power solar plant devices; diagnostic information;All these keywords.
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