Projecting Annual Rainfall Timeseries Using Machine Learning Techniques

Hydropower plays an essential role in Europe’s energy transition and can serve as important factor the stability of electricity system. This is even more crucial areas that rely strongly on renewable production, for instance, solar wind power, example Peloponnese Ionian islands Greece. To safeguard hydropower’s contribution to total accurate prediction annual precipitation required. Valuable tools obtain predictions future observations are firstly a series sophisticated data preprocessing techniques secondly use advanced machine learning algorithms. In present paper, complete procedure proposed meteorological data, such precipitation. applied Greek automated weather stations network, operated by National Observatory Athens, The algorithm successfully identified climatic zones based their different geographic characteristics most stations, resulting realistic predictions. For some underestimated precipitation, weakness also reported other research works.