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Machine Learning-Based Hybrid Algorithms to Forecast Power Generated by Solar Projects

The breakthrough allows day-ahead forecast of power generated by solar PV projects

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Researchers led by Dr. Kalop of Urban Environmental Engineering and Professor Heo Jong-wan from Incheon National University, South Korea, have developed two new machine learning-based models that forecast the power generated by solar projects. Called the adaptive neuro-fuzzy inference system (ANFIS), the advanced models incorporating artificial intelligence efficiently forecast the power generated by photovoltaic systems ahead of time by up to a full day.

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