Zobrazeno 1 - 10
of 132
pro vyhledávání: '"H.F. de Campos Velho"'
Publikováno v:
Trends in Computational and Applied Mathematics, Vol 11, Iss 1 (2010)
Assimilação de Dados é um método que combina dados de um modelo matemático e dados de observações, permitindo uma melhoria na previsão do modelo. Métodos seqüenciais ótimos são baseados em teoria de estimativa formal que minimiza os erros
Externí odkaz:
https://doaj.org/article/1947d410f17146b7ba61af7042a99a2f
Publikováno v:
Trends in Computational and Applied Mathematics, Vol 10, Iss 1 (2009)
Os registros de astronomia ótica constituem uma fonte de informação extremamente importante. Estas medidas são fundamentais para classificar estrelas e galáxias. Este trabalho descreve o algoritmo de construção de árvore de decisão (J4.8) e
Externí odkaz:
https://doaj.org/article/ae761fdb24f4424eb21814db0cbc30f7
Publikováno v:
Trends in Computational and Applied Mathematics, Vol 6, Iss 1 (2005)
Inverse problems in vibration is a process of determining parameters based on numerical analysis from a comparison between measured vibration data and its predicted values provided by a mathematical model. In this work the dis- placement data have be
Externí odkaz:
https://doaj.org/article/66188f238ccf4167ba208e9414872f2b
Publikováno v:
Trends in Computational and Applied Mathematics, Vol 1, Iss 2 (2000)
An important topic in radiative process is the estimation of some characteristics of the media and/or other conditions of the problem.
Externí odkaz:
https://doaj.org/article/ec9c7f28cfe248a58457ec7418b9662b
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Autor:
J. Z. de Mattos, M. A. Gan, A. F. Dos Santos, H.F. de Campos Velho, Georg Grell, Saulo R. Freitas, E. F. P. da Luz
Publikováno v:
Advances in Geosciences, Vol 35, Pp 123-136 (2013)
In this paper we consider an optimization problem applying the metaheuristic Firefly algorithm (FY) to weight an ensemble of rainfall forecasts from daily precipitation simulations with the Brazilian developments on the Regional Atmospheric Modeling
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7e0e379a1b39ac700844beed38b63bea
https://www.adv-geosci.net/35/123/2013/
https://www.adv-geosci.net/35/123/2013/
Publikováno v:
Integral Methods in Science and Engineering, Volume 2 ISBN: 9783319593869
Data mining approach is applied to evaluate extreme rainfall events in the Brazil. Statistical analysis is combined with an artificial intelligence technique to identify the most relevant meteorological variables for a local severe precipitation in t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e672d729fce6f6327aac11c32fce66da
https://doi.org/10.1007/978-3-319-59387-6_22
https://doi.org/10.1007/978-3-319-59387-6_22
Publikováno v:
Integral Methods in Science and Engineering, Volume 2 ISBN: 9783319593869
The numerical weather prediction is a routine in operational meteorological centers, where sophisticated computer models are executed. The atmospheric dynamics is simulated by solving the Navier-Stokes equations, considering several physical phenomen
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::69a794eac7f05d920340a08bf766af45
https://doi.org/10.1007/978-3-319-59387-6_29
https://doi.org/10.1007/978-3-319-59387-6_29
Publikováno v:
Cosmic Research. 48:443-450
The information on the project being developed in Brazil for a flight to binary or triple near-Earth asteroid is presented. The project plans to launch a spacecraft into an orbit around the asteroid and to study the asteroid and its satellite within
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::29d37e5a48ac8509b8d48a90582e73ec
https://doi.org/10.1134/s0010952510050114
https://doi.org/10.1134/s0010952510050114