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Massive feature extraction for explaining and foretelling hydroclimatic time series forecastability at the global scale
Institution:1. Department of Engineering, Roma Tre University, Via V. Volterra 62, 00146 Rome, Italy;2. Department of Water Resources and Environmental Engineering, School of Civil Engineering, National Technical University of Athens, Heroon Polytechneiou 5, 15780 Zographou, Greece;3. Hellenic Air Force General Staff, Hellenic Air Force, Mesogion Avenue 227–231, 15561 Cholargos, Greece;4. Swedish Meteorological and Hydrological Institute, 60176 Norrköping, Sweden;5. Department for Innovation in Biological, Agro‐food and Forest Systems, University of Tuscia, Viterbo, Italy;6. Department of Mechanical and Aerospace Engineering, Tandon School of Engineering, New York University, Brooklyn, NY, 10003, United States
Abstract:
Keywords:Exponential smoothing  Predictability  Statistical hydrology  Time series analysis  Time series clustering  Time series forecasting
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