Learning ensembles of deep neural networks for extreme rainfall event detection
CC BY
Saved in:
Main Authors: | , , |
---|---|
Format: | Book |
Language: | English |
Published: |
Springer
2023
|
Subjects: | |
Online Access: | https://link.springer.com/article/10.1007/s00521-023-08238-0 https://dlib.phenikaa-uni.edu.vn/handle/PNK/8334 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
id |
oai:localhost:PNK-8334 |
---|---|
record_format |
dspace |
spelling |
oai:localhost:PNK-83342023-04-26T06:47:54Z Learning ensembles of deep neural networks for extreme rainfall event detection Gianluigi, Folino Massimo, Guarascio Francesco, Chiaravalloti DeepEns-REM REM CC BY Accurate rainfall estimation is crucial to adequately assess the risk associated with extreme events capable of triggering floods and landslides. Data gathered from Rain Gauges (RGs), sensors devoted to measuring the intensity of the rain at individual points, are commonly used to feed interpolation methods (e.g., the Kriging geostatistical approach) and estimate the precipitation field over an area of interest. However, the information provided by RGs could be insufficient to model complex phenomena, and computationally expensive interpolation methods could not be used in real-time environments. Integrating additional data sources (e.g., radar and geostationary satellites) is an effective solution for improving the quality of the estimate, but it needs to cope with Big Data issues. To overcome all these issues, we propose a Rainfall Estimation Model (REM) based on an Ensemble of Deep Neural Networks (DeepEns-REM) that can automatically fuse heterogeneous data sources. 2023-04-26T06:47:54Z 2023-04-26T06:47:54Z 2023 Book https://link.springer.com/article/10.1007/s00521-023-08238-0 https://dlib.phenikaa-uni.edu.vn/handle/PNK/8334 en application/pdf Springer |
institution |
Digital Phenikaa |
collection |
Digital Phenikaa |
language |
English |
topic |
DeepEns-REM REM |
spellingShingle |
DeepEns-REM REM Gianluigi, Folino Massimo, Guarascio Francesco, Chiaravalloti Learning ensembles of deep neural networks for extreme rainfall event detection |
description |
CC BY |
format |
Book |
author |
Gianluigi, Folino Massimo, Guarascio Francesco, Chiaravalloti |
author_facet |
Gianluigi, Folino Massimo, Guarascio Francesco, Chiaravalloti |
author_sort |
Gianluigi, Folino |
title |
Learning ensembles of deep neural networks for extreme rainfall event detection |
title_short |
Learning ensembles of deep neural networks for extreme rainfall event detection |
title_full |
Learning ensembles of deep neural networks for extreme rainfall event detection |
title_fullStr |
Learning ensembles of deep neural networks for extreme rainfall event detection |
title_full_unstemmed |
Learning ensembles of deep neural networks for extreme rainfall event detection |
title_sort |
learning ensembles of deep neural networks for extreme rainfall event detection |
publisher |
Springer |
publishDate |
2023 |
url |
https://link.springer.com/article/10.1007/s00521-023-08238-0 https://dlib.phenikaa-uni.edu.vn/handle/PNK/8334 |
_version_ |
1764268035088056320 |
score |
8.891787 |