Massive feature extraction for explaining and foretelling hydroclimatic time series forecastability at the global scale

25 July 2021

Papers citing "Massive feature extraction for explaining and foretelling hydroclimatic time series forecastability at the global scale"

6 / 6 papers shown

Title
Comparison of machine learning algorithms for merging gridded satellite and earth-observed precipitation data Georgia Papacharalampous Hristos Tyralis Anastasios Doulamis N. Doulamis 32 15 0 17 Dec 2022
A review of machine learning concepts and methods for addressing challenges in probabilistic hydrological post-processing and forecasting Georgia Papacharalampous Hristos Tyralis AI4CE 32 28 0 17 Jun 2022
Features of the Earth's seasonal hydroclimate: Characterizations and comparisons across the Koppen-Geiger climates and across continents Georgia Papacharalampous Hristos Tyralis Y. Markonis P. Máca M. Hanel BDL 21 0 0 13 Apr 2022
Time series features for supporting hydrometeorological explorations and predictions in ungauged locations using large datasets Georgia Papacharalampous Hristos Tyralis AI4TS 28 10 0 13 Apr 2022
Hydroclimatic time series features at multiple time scales Georgia Papacharalampous Hristos Tyralis Y. Markonis M. Hanel AI4TS 27 3 0 02 Dec 2021
Global-scale massive feature extraction from monthly hydroclimatic time series: Statistical characterizations, spatial patterns and hydrological similarity Georgia Papacharalampous Hristos Tyralis S. Papalexiou A. Langousis S. Khatami E. Volpi S. Grimaldi 30 32 0 24 Oct 2020