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Forecasting of Dry Freight Index Data by Using Machine Learning Algorithms

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dc.contributor.authorAkyol, Kemal
dc.date.accessioned2026-01-04T13:22:30Z
dc.date.issued2019-08-08
dc.description.urihttps://doi.org/10.5815/ijisa.2019.08.04
dc.description.urihttp://www.mecs-press.org/ijisa/ijisa-v11-n8/IJISA-V11-N8-4.pdf
dc.description.urihttps://dx.doi.org/10.5815/ijisa.2019.08.04
dc.identifier.doi10.5815/ijisa.2019.08.04
dc.identifier.eissn2074-9058
dc.identifier.endpage43
dc.identifier.issn2074-904X
dc.identifier.openairedoi_dedup___::cbf4f514a8858943ccd843137c263d08
dc.identifier.startpage35
dc.identifier.urihttps://hdl.handle.net/20.500.12597/37450
dc.identifier.volume11
dc.publisherMECS Publisher
dc.relation.ispartofInternational Journal of Intelligent Systems and Applications
dc.rightsOPEN
dc.titleForecasting of Dry Freight Index Data by Using Machine Learning Algorithms
dc.typeArticle
dspace.entity.typePublication
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