@InProceedings{NowosadCampRios:2000:NeNeNe,
author = "Nowosad, A. G. and Campos Velho, H. F. de and Rios Neto, A.",
affiliation = "{INPE-Sao Jose dos Campos-12227-010-SP-Brasil}",
title = "Neural network as a new approach for data assimilation",
booktitle = "Anais...",
year = "2000",
pages = "3078--3086",
organization = "Congresso Brasileiro de Meteorologia, 11.",
keywords = "data assimilation, neural networks, Kalman filter, nonlinear
dynamics.",
abstract = "Multilayer Perceptron Neural Networks are tested as a new method
for data assimilation in DYNAMO meteorological model. The approach
{"}emulates{"} the Kalman Filter data assimilation method avoiding
recalculation of the gain matrix at each instant of assimilation.
A new prodedure for training the networks is also presented, based
on a modification in the backpropagation algorithm. An Adaptive
Extended Kalman Filter was used to provide examples for network
training.",
conference-location = "Rio de Janeiro",
conference-year = "16-20 out. 2000",
copyholder = "SID/SCD",
language = "pt",
organisation = "SBMET",
targetfile = "PT00002.PDF",
urlaccessdate = "29 jun. 2024"
}