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Conversion methods of data mining analysis in algorithms of statistical and nowcasting forecast of convective precipitation

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dc.title Conversion methods of data mining analysis in algorithms of statistical and nowcasting forecast of convective precipitation en
dc.contributor.author Šaur, David
dc.contributor.author Švejda, Jaromír
dc.relation.ispartof Lecture Notes in Networks and Systems
dc.identifier.issn 2367-3370 Scopus Sources, Sherpa/RoMEO, JCR
dc.identifier.isbn 978-3-03-077441-7
dc.date.issued 2021
utb.relation.volume 230
dc.citation.spage 437
dc.citation.epage 450
dc.event.title 10th Computer Science Online Conference, CSOC 2021
dc.event.location online
dc.event.sdate 2021-04-01
dc.event.edate 2021-04-01
dc.type conferenceObject
dc.language.iso en
dc.publisher Springer Science and Business Media Deutschland GmbH
dc.identifier.doi 10.1007/978-3-030-77442-4_38
dc.relation.uri https://link.springer.com/chapter/10.1007/978-3-030-77442-4_38
dc.subject algorithm en
dc.subject convective precipitation en
dc.subject conversion methods en
dc.subject crisis management en
dc.subject Ddata mining en
dc.subject radar measurement en
dc.subject weather forecast en
dc.description.abstract This article focuses on the description of computational methods for the conversion of products for the purposes of calculating the statistical and nowcasting prediction of convective precipitation. Convective precipitation can reach very high intensities and cause flash floods, which can endanger human lives and health and cause material damage on a local scale. The methodological part describes computational methods designed for the conversion of input data, which are radar products CAPPI and VIL, including the combined product SUM MERGE. The resulting part is focused on the evaluation of these computational methods, where the outputs of this evaluation are applied to the conversion algorithm. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG. en
utb.faculty Faculty of Applied Informatics
dc.identifier.uri http://hdl.handle.net/10563/1010520
utb.identifier.scopus 2-s2.0-85113386576
utb.source d-scopus
dc.date.accessioned 2021-09-06T20:39:29Z
dc.date.available 2021-09-06T20:39:29Z
utb.contributor.internalauthor Šaur, David
utb.contributor.internalauthor Švejda, Jaromír
utb.scopus.affiliation Faculty of Applied Informatics, Tomas Bata University in Zlin, Nad Stranemi, Zlín, 4511, Czech Republic
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