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Time series features for supporting hydrometeorological explorations and
  predictions in ungauged locations using large datasets
v1v2 (latest)

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

13 April 2022
Georgia Papacharalampous
Hristos Tyralis
    AI4TS
ArXiv (abs)PDFHTML

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

2 / 2 papers shown
Title
Comparison of tree-based ensemble algorithms for merging satellite and
  earth-observed precipitation data at the daily time scale
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
104
11
0
31 Dec 2022
Comparison of machine learning algorithms for merging gridded satellite
  and earth-observed precipitation data
Comparison of machine learning algorithms for merging gridded satellite and earth-observed precipitation data
Georgia Papacharalampous
Hristos Tyralis
Anastasios Doulamis
N. Doulamis
68
15
0
17 Dec 2022
1