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http://acervodigital.unesp.br/handle/11449/36961
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DC Field | Value | Language |
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dc.contributor.author | Ulson, Jose Alfredo Covolan | - |
dc.contributor.author | Antonio, MDA | - |
dc.contributor.author | Da Silva, I. N. | - |
dc.contributor.author | De Souza, A. N. | - |
dc.contributor.author | Callaos, N. | - |
dc.contributor.author | DaSilva, I. N. | - |
dc.contributor.author | Molero, J. | - |
dc.date.accessioned | 2014-05-20T15:26:53Z | - |
dc.date.accessioned | 2016-10-25T18:01:34Z | - |
dc.date.available | 2014-05-20T15:26:53Z | - |
dc.date.available | 2016-10-25T18:01:34Z | - |
dc.date.issued | 2001-01-01 | - |
dc.identifier | http://dl.acm.org/citation.cfm?id=704229 | - |
dc.identifier.citation | World Multiconference on Systemics, Cybernetics and Informatics, Vol 1, Proceedings. Orlando: Int Inst Informatics & Systemics, p. 30-34, 2001. | - |
dc.identifier.uri | http://hdl.handle.net/11449/36961 | - |
dc.identifier.uri | http://acervodigital.unesp.br/handle/11449/36961 | - |
dc.description.abstract | This work presents a new approach for rainfall measurements making use of weather radar data for real time application to the radar systems operated by institute of Meteorological Research (IPMET) - UNESP - Bauru - SP-Brazil. Several real time adjustment techniques has been presented being most of them based on surface rain-gauge network. However, some of these methods do not regard the effect of the integration area, time integration and distance rainfall-radar. In this paper, artificial neural networks have been applied for generate a radar reflectivity-rain relationships which regard all effects described above. To evaluate prediction procedure, cross validation was performed using data from IPMET weather Doppler radar and rain-gauge network under the radar umbrella. The preliminary results were acceptable for rainfalls prediction. The small errors observed result from the spatial density and the time resolution of the rain-gauges networks used to calibrate the radar. | en |
dc.format.extent | 30-34 | - |
dc.language.iso | eng | - |
dc.publisher | Int Inst Informatics & Systemics | - |
dc.source | Web of Science | - |
dc.subject | rainfall | pt |
dc.subject | radar | pt |
dc.subject | Z-R relationships | pt |
dc.subject | artificial neural network | pt |
dc.title | An intelligent system to real time rainfall prediction using radar data | en |
dc.type | outro | - |
dc.contributor.institution | Universidade Estadual Paulista (UNESP) | - |
dc.description.affiliation | São Paulo State Univ, Dept Elect Engn, BR-17100 Bauru, SP, Brazil | - |
dc.description.affiliationUnesp | São Paulo State Univ, Dept Elect Engn, BR-17100 Bauru, SP, Brazil | - |
dc.identifier.wos | WOS:000175785900006 | - |
dc.rights.accessRights | Acesso restrito | - |
dc.relation.ispartof | World Multiconference on Systemics, Cybernetics and Informatics, Vol 1, Proceedings | - |
Appears in Collections: | Artigos, TCCs, Teses e Dissertações da Unesp |
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