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dc.contributor.authorŞen, Zekai
dc.date.accessioned2020-04-20T11:03:56Z
dc.date.available2020-04-20T11:03:56Z
dc.date.issued2020en_US
dc.identifier.citationŞen, Z. (2020). Probabilistic innovative trend analysis. International Journal of Global Warming, 20(2), 93-105. https://dx.doi.org/10.1504/IJGW.2020.105387en_US
dc.identifier.issn1758-2083
dc.identifier.issn1758-2091
dc.identifier.urihttps://hdl.handle.net/20.500.12511/5175
dc.identifier.urihttps://dx.doi.org/10.1504/IJGW.2020.105387
dc.description.abstractThis paper proposes new methodology for trend analysis, named as the probabilistic innovative trend analysis (PITA), whereby instead of statistical parameters probability distribution functions play the major role. The basis of the methodology is to compare the cumulative probability distribution functions (CDF) for each half of a given hydro-meteorological records. The methodology is without any restrictive assumption. The application of the PITA methodology is presented for Danube River discharge, New Jersey statewise precipitation and Istanbul minimum temperature records.en_US
dc.language.isoengen_US
dc.publisherInderscience Enterprises Ltd.en_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectClimate Changeen_US
dc.subjectClimate Variabilityen_US
dc.subjectİnnovationen_US
dc.subjectProbabilityen_US
dc.subjectTrenden_US
dc.subjectTime Seriesen_US
dc.titleProbabilistic innovative trend analysisen_US
dc.typearticleen_US
dc.relation.ispartofInternational Journal of Global Warmingen_US
dc.departmentİstanbul Medipol Üniversitesi, Mühendislik ve Doğa Bilimleri Fakültesi, İnşaat Mühendisliği Bölümüen_US
dc.authorid0000-0003-2754-5492en_US
dc.identifier.volume20en_US
dc.identifier.issue2en_US
dc.identifier.startpage93en_US
dc.identifier.endpage105en_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.identifier.doi10.1504/IJGW.2020.105387en_US
dc.identifier.wosqualityQ4en_US
dc.identifier.scopusqualityQ3en_US


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