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    Master Thesis
    Short-Term Solar Irradiance Forecasting With Deep Neural Networks
    (Kadir Has Üniversitesi, 2019) Vatansever, Caner; Ceylan, Oğuzhan; Ceylan, O?uzhan; Management Information Systems
    Usage of solar energy has increased through the last decades, and they are being integrated into main grid systems since the recent years. In order to fully bene t from solar panels, predicting irradiance is essential. By knowing 15-minute ahead values of solar irradiance, resistance of the cells inside the solar panels can be measured to analyze production output. This study focuses on 15-minute ahead forecasting of irradiance by using sliding windows method on the feature set. ANN, K-NN, SVM and RF models are optimized in this study. As the result of the study, around 6% MAPE is achieved