A comparison of multiple regression and artificial neural networks approaches to identifying significant contributors to project performance levels

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dc.contributor.authorDissanayaka, S.M.
dc.contributor.authorKumaraswamy, M.M.
dc.date.accessioned2020-11-30T03:56:17Z
dc.date.available2020-11-30T03:56:17Z
dc.date.issued1998
dc.identifier.citationEngineer, 27(1):p.23-37
dc.identifier.urihttps://dl-iesl.nsf.gov.lk/handle/1/2599
dc.publisherInstitution of Engineers:Colombo
dc.subjectEngineering and Technology
dc.subjectBuilding construction
dc.subjectProjects
dc.subjectHong Kong
dc.subjectMultiple regression
dc.subjectArtificial Neural Network
dc.titleA comparison of multiple regression and artificial neural networks approaches to identifying significant contributors to project performance levels
dc.typeArticle

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