Výsledky vyhledávání - "Dottori, Marcelo"

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A Physics-Informed Neural Network to Model Port Channels

Autor: Mathias, Marlon S., de Barros, Marcel R., Coelho, Jefferson F., de Freitas, Lucas P., Moreno, Felipe M., Netto, Caio F. D., Cozman, Fabio G., Costa, Anna H. R., Tannuri, Eduardo A., Gomi, Edson S., Dottori, Marcelo

We describe a Physics-Informed Neural Network (PINN) that simulates the flow induced by the astronomical tide in a synthetic port channel, with dimensions based on the Santos - S\~ao Vicente - Bertioga Estuarine System. PINN models aim to combine the

Externí odkaz: http://arxiv.org/abs/2212.10681

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Enhancing Oceanic Variables Forecast in the Santos Channel by Estimating Model Error with Random Forests

Autor: Moreno, Felipe M., Netto, Caio F. D., de Barros, Marcel R., Coelho, Jefferson F., de Freitas, Lucas P., Mathias, Marlon S., Neto, Luiz A. Schiaveto, Dottori, Marcelo, Cozman, Fabio G., Costa, Anna H. R., Gomi, Edson S., Tannuri, Eduardo A.

In this work we improve forecasting of Sea Surface Height (SSH) and current velocity (speed and direction) in oceanic scenarios. We do so by resorting to Random Forests so as to predict the error of a numerical forecasting system developed for the Sa

Externí odkaz: http://arxiv.org/abs/2208.05966

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Modeling Oceanic Variables with Dynamic Graph Neural Networks

Autor: Netto, Caio F. D., de Barros, Marcel R., Coelho, Jefferson F., de Freitas, Lucas P., Moreno, Felipe M., Mathias, Marlon S., Dottori, Marcelo, Cozman, Fábio G., Costa, Anna H. R., Gomi, Edson S., Tannuri, Eduardo A.

Researchers typically resort to numerical methods to understand and predict ocean dynamics, a key task in mastering environmental phenomena. Such methods may not be suitable in scenarios where the topographic map is complex, knowledge about the under

Externí odkaz: http://arxiv.org/abs/2206.12746

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