Decision tree regression model to predict low-rank coal moisture content during convective drying process

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dc.authoridPEKEL, Engin / 0000-0002-5295-8013
dc.authoridAkkoyunlu, Mehmet Cabir / 0000-0002-9388-6554
dc.authoridPusat, Saban / 0000-0001-5868-4503
dc.authorwosidakkoyunlu, mehmet cabir / AAK-4612-2021
dc.authorwosidPusat, Saban / AAZ-5375-2020
dc.contributor.authorPekel, Engin
dc.contributor.authorAkkoyunlu, Mehmet Cabir
dc.contributor.authorAkkoyunlu, Mustafa Tahir
dc.contributor.authorPusat, Saban
dc.date.accessioned2021-11-01T15:05:13Z
dc.date.available2021-11-01T15:05:13Z
dc.date.issued2020
dc.department[Belirlenecek]
dc.description.abstractCoal is still a significant energy source for the world. Due to the utilization of low-rank coal, drying is a key issue. There are lots of attempts to develop efficient drying processes. The most prominent method seems as thermal drying. For thermal drying processes, the most important subject is the coal moisture content change with time. In this study, convective drying experiments were utilized to develop a new model based on decision tree regression method to predict coal moisture content. The developed model gives satisfactory results in prediction of instant coal moisture content with changing drying conditions. With the decision tree depth of six, the best test results were achieved as 0.056 and 0.802 for MSE and R-2 analyses, respectively.
dc.identifier.doi10.1080/19392699.2020.1737527
dc.identifier.endpage512en_US
dc.identifier.issn1939-2699
dc.identifier.issn1939-2702
dc.identifier.issue8en_US
dc.identifier.scopus2-s2.0-85081742769
dc.identifier.scopusqualityQ2
dc.identifier.startpage505en_US
dc.identifier.urihttps://doi.org/10.1080/19392699.2020.1737527
dc.identifier.urihttps://hdl.handle.net/11491/7174
dc.identifier.volume40en_US
dc.identifier.wosWOS:000519514800001
dc.identifier.wosqualityQ2
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthor[Belirlenecek]
dc.language.isoen
dc.publisherTaylor & Francis Inc
dc.relation.ispartofInternational Journal Of Coal Preparation And Utilization
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectDecision tree regressionen_US
dc.subjectcoal dryingen_US
dc.subjectmoisture contenten_US
dc.subjectlow-rank coalen_US
dc.titleDecision tree regression model to predict low-rank coal moisture content during convective drying process
dc.typeArticle

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