@InProceedings{VelhoHärt:2009:PrReNe,
author = "Velho, Haroldo de Campos and H{\"a}rter, Fabr{\'{\i}}cio P.",
affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {National
Institute of Meteorology (INMet)}",
title = "Preliminary results with neural network for data assimilation to
the space weather",
booktitle = "Proceedings...",
year = "2009",
editor = "Scientific and Sawant, Hanumant Shankar and Rao, A. Pramesh and
Gopalswamy, Natchimuthukonar and Hurford, Gordon J. and
Ananthakrishnan, Subramaniam and Executive and Fernandes,
Francisco Carlos Rocha and Moraes, Lu¨ªs Cesar Pereira de",
pages = "161--168",
organization = "Brazilian Decimetric Array Workshop.",
publisher = "INPE",
address = "S{\~a}o Jos{\'e} dos Campos",
keywords = "NEURAL, NETWORK, ASSIMILATION, SPACE, WEATHER.",
abstract = "Data assimilation is an essential step for improving space weather
operational forecasting by means of an appropriated combination
between observational data and data from a mathematical model. In
the present work data assimilation methods based on Kalman filter
and artificial neural networks are applied to a three-wave model
of auroral radio emissions. A novel data assimilation method is
presented, whereby a multilayer perceptron neural network is
trained to emulate a Kalman filter for data assimilation by using
cross validation. The results obtained render support for the use
of neural networks as an assimilation technique for space weather
prediction.",
conference-location = "INPE",
conference-year = "July 28 ¨C August 1, 2008",
language = "en",
ibi = "8JMKD3MGP8W/35LT4CB",
url = "http://urlib.net/ibi/8JMKD3MGP8W/35LT4CB",
targetfile = "BDA_proc25_Haroldo.pdf",
urlaccessdate = "12 maio 2024"
}