Publication Date:
2023-02-28
Description:
In a period in which climate change is signifcantly varying rainfall regimes and their intensity all over the world, river-fow
prediction is a major concern of geosciences. In recent years there has been an increase in the use of deep-learning models
for river-fow prediction. However, in this feld we can observe two main issues: i) many case studies use similar (or the
same) strategies without sharing the codes, and ii) the application of these techniques requires good computer knowledge.
This work proposes to employ a Google Colab notebook called CleverRiver, which allows the application of deep-learning
for river-fow predictions. CleverRiver is a dynamic software that can be upgraded and modifed not only by the authors but
also by the users. The main advantages of CleverRiver are the following: the software is not limited by the client hardware,
operating systems, etc.; the code is open-source; the toolkit is integrated with user-friendly interfaces; updated releases with
new architectures, data management, and model parameters will be progressively uploaded. The software consists of three
sections: the frst one enables to train the models by means of some architectures, parameters, and data; the second section
allows to create predictions by using the trained models; the third section allows to send feedback and to share experiences
with the authors, providing a fux of precious information able to improve scientifc research.
Description:
Published
Description:
1119–1130
Description:
3IT. Calcolo scientifico
Description:
JCR Journal
Repository Name:
Istituto Nazionale di Geofisica e Vulcanologia (INGV)
Type:
article
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