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dc.contributor.authorUlson, Jose Alfredo Covolan-
dc.contributor.authorAntonio, MDA-
dc.contributor.authorDa Silva, I. N.-
dc.contributor.authorDe Souza, A. N.-
dc.contributor.authorCallaos, N.-
dc.contributor.authorDaSilva, I. N.-
dc.contributor.authorMolero, J.-
dc.date.accessioned2014-05-20T15:26:53Z-
dc.date.accessioned2016-10-25T18:01:34Z-
dc.date.available2014-05-20T15:26:53Z-
dc.date.available2016-10-25T18:01:34Z-
dc.date.issued2001-01-01-
dc.identifierhttp://dl.acm.org/citation.cfm?id=704229-
dc.identifier.citationWorld Multiconference on Systemics, Cybernetics and Informatics, Vol 1, Proceedings. Orlando: Int Inst Informatics & Systemics, p. 30-34, 2001.-
dc.identifier.urihttp://hdl.handle.net/11449/36961-
dc.identifier.urihttp://acervodigital.unesp.br/handle/11449/36961-
dc.description.abstractThis 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.extent30-34-
dc.language.isoeng-
dc.publisherInt Inst Informatics & Systemics-
dc.sourceWeb of Science-
dc.subjectrainfallpt
dc.subjectradarpt
dc.subjectZ-R relationshipspt
dc.subjectartificial neural networkpt
dc.titleAn intelligent system to real time rainfall prediction using radar dataen
dc.typeoutro-
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)-
dc.description.affiliationSão Paulo State Univ, Dept Elect Engn, BR-17100 Bauru, SP, Brazil-
dc.description.affiliationUnespSão Paulo State Univ, Dept Elect Engn, BR-17100 Bauru, SP, Brazil-
dc.identifier.wosWOS:000175785900006-
dc.rights.accessRightsAcesso restrito-
dc.relation.ispartofWorld Multiconference on Systemics, Cybernetics and Informatics, Vol 1, Proceedings-
Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

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