Artificial Neural Networks emulating Representer Method at a shallow water model 2D

Autores

  • Helaine Furtado
  • Rosângela Cintra
  • Haroldo de Campos Velho

DOI:

https://doi.org/10.5540/03.2016.004.01.0097

Palavras-chave:

Data assimilation, differential equations, numerical prediction, artificial neural networks, representer method.

Resumo

The goal of the present work is to employ artificial neural networks as a data assimilation method applied to shallow water equation. This model is used to represent ocean dynamics. Data assimilation is a computational procedure to combine observation data with model data for identifying the best initial condition (analysis) to an operational prediction system. Here we compare two techniques: representer method and artificial neural network.

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Publicado

2016-08-09

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