Browsing by Author "Hulak, D."

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    Machine learning techniques for the energy generation analysis and prediction
    (National Aviation University, 2024-03) Hulak, D.; Гулак, Д
    The global energy landscape is rapidly shifting towards renewable sources, notably photovoltaic (PV) installations. However, the PV reliance on meteorological conditions poses challenges to grid stability. Leveraging machine learning (ML) models offers a promising solution by accurately predicting energy generation. ML's ability to tackle complex patterns and continuously learn from historical data enables the development of adaptive forecasting models, enhancing the efficiency of PV installations and advancing sustainable energy practices.