Time series features for supporting hydrometeorological explorations and predictions in ungauged locations using large datasets

13 April 2022

Papers citing "Time series features for supporting hydrometeorological explorations and predictions in ungauged locations using large datasets"

6 / 6 papers shown

Title
Merging satellite and gauge-measured precipitation using LightGBM with an emphasis on extreme quantiles Hristos Tyralis Georgia Papacharalampous N. Doulamis Anastasios Doulamis 21 7 0 02 Feb 2023
Comparison of tree-based ensemble algorithms for merging satellite and earth-observed precipitation data at the daily time scale Georgia Papacharalampous Hristos Tyralis Anastasios Doulamis N. Doulamis 59 11 0 31 Dec 2022
Comparison of machine learning algorithms for merging gridded satellite and earth-observed precipitation data Georgia Papacharalampous Hristos Tyralis Anastasios Doulamis N. Doulamis 27 15 0 17 Dec 2022
Hydroclimatic time series features at multiple time scales Georgia Papacharalampous Hristos Tyralis Y. Markonis M. Hanel AI4TS 21 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 22 32 0 24 Oct 2020
ranger: A Fast Implementation of Random Forests for High Dimensional Data in C++ and R Marvin N. Wright A. Ziegler 93 2,732 0 18 Aug 2015