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Modeling the productivity of mechanized CTL harvesting with statistical machine learning methods

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dc.contributor.authorLiski, Eero
dc.contributor.authorJounela, Pekka
dc.contributor.authorKorpunen, Heikki
dc.contributor.authorSosa, Amanda
dc.contributor.authorLindroos, Ola
dc.contributor.authorJylhä, Paula
dc.contributor.departmentid4100111010
dc.contributor.departmentid4100210610
dc.contributor.departmentid4100210610
dc.contributor.departmentid4100111010
dc.contributor.organizationLuonnonvarakeskus
dc.date.accessioned2021-01-05T06:31:34Z
dc.date.accessioned2025-05-28T14:44:42Z
dc.date.available2021-01-05T06:31:34Z
dc.date.issued2020
dc.description.vuosik2020
dc.format.bitstreamfalse
dc.format.pagerange253-262
dc.identifier.olddbid489429
dc.identifier.oldhandle10024/546889
dc.identifier.urihttps://jukuri.luke.fi/handle/11111/25482
dc.language.isoen
dc.okm.corporatecopublicationei
dc.okm.discipline4112
dc.okm.internationalcopublicationon
dc.okm.openaccess2 = Hybridijulkaisukanavassa ilmestynyt avoin julkaisu
dc.okm.selfarchivedei
dc.publisherTaylor & Francis in partnership with Forest Products Society
dc.relation.doi10.1080/14942119.2020.1820750
dc.relation.ispartofseriesInternational journal of forest engineering
dc.relation.issn1494-2119
dc.relation.issn1913-2220
dc.relation.numberinseries3
dc.relation.volume31
dc.source.identifierhttps://jukuri.luke.fi/handle/10024/546889
dc.subject.ysoproductivity
dc.subject.ysocut-to-length
dc.subject.ysoharvester
dc.subject.ysomachine learning
dc.subject.ysogradient boosted machine
dc.subject.ysosupport vector machine
dc.subject.ysoregression model
dc.teh41007-00106103
dc.titleModeling the productivity of mechanized CTL harvesting with statistical machine learning methods
dc.typepublication
dc.type.okmfi=A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä|sv=A1 Originalartikel i en vetenskaplig tidskrift|en=A1 Journal article (refereed), original research|

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