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This study presents a method for diagnosing faults in photovoltaic panels using artificial neural networks (ANN), which detects power loss due to temperature and solar irradiance fluctuations. By creating a baseline model of normal operation, the ANN can accurately identify anomalies in real-time, enhancing maintenance efficiency and system reliability. The results indicate high precision in fault detection, demonstrating the effectiveness of this intelligent diagnostic approach without the need for complex

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rofiafcb

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EN