Discovery of hydrometeorological patterns

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dc.authorid0000-0002-1775-0954
dc.contributor.authorCelik, Mete
dc.contributor.authorDadaser-Celik, Filiz
dc.contributor.authorDokuz, Ahmet Sakir
dc.date.accessioned2019-08-01T13:38:39Z
dc.date.available2019-08-01T13:38:39Z
dc.date.issued2014
dc.departmentNiğde ÖHÜ
dc.description.abstractHydrometeorological patterns can be defined as meaningful and nontrivial associations between hydrological and meteorological parameters over a region. Discovering hydrometeorological patterns is important for many applications, including forecasting hydrometeorological hazards (floods and droughts), predicting the hydrological responses of ungauged basins, and filling in missing hydrological or meteorological records. However, discovering these patterns is challenging due to the special characteristics of hydrological and meteorological data, and is computationally complex due to the archival history of the datasets. Moreover, defining monotonic interest measures to quantify these patterns is difficult. In this study, we propose a new monotonic interest measure, called the hydrometeorological prevalence index, and a novel algorithm for mining hydrometeorological patterns (HMP-Miner) out of large hydrological and meteorological datasets. Experimental evaluations using real datasets show that our proposed algorithm outperforms the naive alternative in discovering hydrometeorological patterns efficiently.
dc.description.sponsorshipScientific and Technological Research Council of Turkey (TUBITAK) [CAYDAG 110Y110]; Research Fund of Erciyes University [FBA-09-866]
dc.description.sponsorshipThis study was partially supported by the Scientific and Technological Research Council of Turkey (TUBITAK), Project Number: CAYDAG 110Y110 and the Research Fund of Erciyes University, Project Number: FBA-09-866. We would like to thank Eda Cengiz for her help at the data preparation and quality assessment steps.
dc.identifier.doi10.3906/elk-1210-20
dc.identifier.endpage857
dc.identifier.issn1300-0632
dc.identifier.issn1303-6203
dc.identifier.issue4
dc.identifier.scopus2-s2.0-84902122059
dc.identifier.scopusqualityQ3
dc.identifier.startpage840
dc.identifier.urihttps://dx.doi.org/10.3906/elk-1210-20
dc.identifier.urihttps://hdl.handle.net/11480/4251
dc.identifier.volume22
dc.identifier.wosWOS:000337376500003
dc.identifier.wosqualityQ4
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthor[0-Belirlenecek]
dc.language.isoen
dc.publisherTUBITAK SCIENTIFIC & TECHNICAL RESEARCH COUNCIL TURKEY
dc.relation.ispartofTURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectData mining
dc.subjecthydrometeorological pattern
dc.subjectassociation rule mining
dc.subjecthydrological databases
dc.subjectmeteorological databases
dc.titleDiscovery of hydrometeorological patterns
dc.typeArticle

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