OUZONE, M Yann-Ilya (2023) Contribution of piezometric data to artificial intelligence-based hydrological models. PRE - Research Project, ENSTA.

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Abstract

This study aims to investigate the impact of piezometric data in modeling the discharge at the outlet of the watershed using artificial intelligence tools. After a thorough study and representation of the data, correlations between piezometric and discharge data were highlighted. The objective was then to translate this graphical correlation into models. A comparative study showed that the random forest model was effective for our dataset. Finally, the study demonstrated that the models achieved very good performance in simulation, but this performance degraded when transitioning to prediction.

Item Type:Thesis (PRE - Research Project)
Uncontrolled Keywords:Réseaux de neurones
Subjects:Earth Sciences and Environmental Engineering
ID Code:9440
Deposited By:Yann-ilya OUZONE
Deposited On:22 août 2023 14:29
Dernière modification:22 août 2023 14:29

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