A new regression based software cost estimation model using power values

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dc.contributor.authorAdalier, Oktay
dc.contributor.authorUgur, Aybars
dc.contributor.authorKorukoglu, Serdar
dc.contributor.authorErtas, Kadir
dc.contributor.editorYin, H
dc.contributor.editorTino, P
dc.contributor.editorCorchado, E
dc.contributor.editorByrne, W
dc.contributor.editorYao, X
dc.date.accessioned2019-10-27T19:37:59Z
dc.date.available2019-10-27T19:37:59Z
dc.date.issued2007
dc.departmentEge Üniversitesien_US
dc.description8th International Conference on Intelligent Data Engineering and Automated Learning -- DEC 16-19, 2007 -- Birmingham, ENGLANDen_US
dc.description.abstractThe paper aims to provide for the improvement of software estimation research through a new regression model. The study design of the paper is organized as follows. Evaluation of estimation methods based on historical data sets requires that these data sets be representative for current or future projects. For that reason the data set for software cost estimation model the International Software Benchmarking Standards Group (ISBSG) data set Release 9 is used. The data set records true project values in the real world, and can be used to extract information to predict new projects cost in terms of effort. As estimation method regression models are used. The main contribution of this study is the new cost production function that is used to obtain software cost estimation. The new proposed cost estimation function performance is compared with related work in the literature. In the study same calibration on the production function is made in order to obtain maximum performance. There is some important discussion on how the results can be improved and how they can be applied to other estimation models and datasets.en_US
dc.identifier.endpage+en_US
dc.identifier.isbn978-3-540-77225-5
dc.identifier.issn0302-9743
dc.identifier.issn1611-3349
dc.identifier.issn0302-9743en_US
dc.identifier.issn1611-3349en_US
dc.identifier.scopusqualityQ3en_US
dc.identifier.startpage326en_US
dc.identifier.urihttps://hdl.handle.net/11454/40034
dc.identifier.volume4881en_US
dc.identifier.wosWOS:000252394900034en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.language.isoenen_US
dc.publisherSpringer-Verlag Berlinen_US
dc.relation.ispartofIntelligent Data Engineering and Automated Learning - Ideal 2007en_US
dc.relation.ispartofseriesLecture Notes in Computer Science
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectsoftware cost estimationen_US
dc.subjectregression analysisen_US
dc.subjectsoftware cost modelsen_US
dc.titleA new regression based software cost estimation model using power valuesen_US
dc.typeConference Objecten_US

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