Work

Scripts for the paper "Which strategy to improve the performances of an LSTM-based model for extreme stream temperature values?"

Year: 2025

Type: article

Abstract: This folder contains three scripts to train and evaluate a locally trained LSTM model and a regionally trained LSTM model for stream temperature. It also contains a file of the results of all the trained and tested models presented in the paper.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.15864783

Author: Saadi, Mohamed

Institutions: Institut National Polytechnique de Toulouse, Institut de Mécanique des Fluides de Toulouse, Université de Toulouse

Language: English

Topic: Hydrological Forecasting Using AI

Subfield: Environmental Engineering

Field: Environmental Science

Domain: Physical Sciences

SDG: Climate action

Open Access status: green

OpenAlex ID: W6912037196

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