Yayın:
Predictions of oil/chemical tanker main design parameters using computational intelligence techniques

dc.contributor.authorEkinci, S.
dc.contributor.authorCelebi, U. B.
dc.contributor.authorBal, M.
dc.contributor.authorAmasyali, M. F.
dc.contributor.authorBoyaci, U. K.
dc.contributor.institutionauthorAMASYALI, Mehmet Fatih
dc.date.accessioned2026-06-27T13:15:12Z
dc.date.issued2011
dc.description.abstractShip design and construction are complicated and expensive processes. In the pre-design stage, before the construction according to some special rules, determination of the main ship parameters is very important. In this study, instead of traditional methods, the oil/chemical tanker main design parameters are estimated by 18 computational intelligence methods. Therefore, all the data of 114 tankers in operation are used in the experiments in order to estimate a parameter from the remaining ones. Main result of this article is to show that, except for the speed parameter, the main parameters of tankers can be estimated sufficiently well for pre-design stage without having to apply conventional but arduous ship modeling experiments. (C) 2010 Elsevier B.V. All rights reserved.en
dc.description.urihttps://doi.org/10.1016/j.asoc.2010.08.015
dc.identifier.doi10.1016/j.asoc.2010.08.015
dc.identifier.eissn1872-9681
dc.identifier.endpage2366
dc.identifier.issn1568-4946
dc.identifier.issue2
dc.identifier.startpage2356
dc.identifier.urihttps://hdl.handle.net/20.500.14981/51069
dc.identifier.volume11
dc.identifier.wos000286373200087
dc.language.isoeng
dc.publisherELSEVIER
dc.relation.ispartofAPPLIED SOFT COMPUTING
dc.subjectComputational intelligence
dc.subjectMachine learning
dc.subjectNeural networks
dc.subjectNaval engineering
dc.subjectShip design main parameters
dc.subjectIDENTIFICATION
dc.subjectSHIPS
dc.subjectComputer Science
dc.titlePredictions of oil/chemical tanker main design parameters using computational intelligence techniques
dc.typeArticle
dspace.entity.typePublication
local.import.sourceWOS

Dosyalar

Koleksiyonlar