Please use this identifier to cite or link to this item: https://ktisis.cut.ac.cy/handle/10488/3844
DC FieldValueLanguage
dc.contributor.authorPapatheocharous, Efi-
dc.contributor.authorAndreou, Andreas S.-
dc.contributor.otherΑνδρέου, Ανδρέας Σ.-
dc.date2010en
dc.date.accessioned2014-07-10T07:20:46Z-
dc.date.accessioned2015-12-09T12:01:56Z-
dc.date.available2014-07-10T07:20:46Z-
dc.date.available2015-12-09T12:01:56Z-
dc.date.issued2010-10-
dc.identifier.citation6th IFIP WG 12.5 International Conference, Larnaca, Cyprus, 6-7 October, 2010.en_US
dc.identifier.issn1868-4238-
dc.identifier.urihttp://ktisis.cut.ac.cy/handle/10488/3844-
dc.description.abstractMany parameters affect the cost evolution of software projects. In the area of software cost estimation and project management the main challenge is to understand and quantify the effect of these parameters, or 'cost drivers', on the effort expended to develop software systems. This paper aims at investigating the effect of cost attributes on software development effort using empirical databases of completed projects and building Artificial Neural Network (ANN) models to predict effort. Prediction performance of various ANN models with different combinations of inputs is assessed in an attempt to reduce the models' input dimensions. The latter is performed by using one of the most popular saliency measures of network weights, namely Garson's Algorithm. The proposed methodology provides an insight on the interpretation of ANN which may be used for capturing nonlinear interactions between variables in complex software engineering environments.en_US
dc.formatpdfen_US
dc.languageenen
dc.language.isoenen_US
dc.publisherSpringer Berlin Heidelberg-
dc.rightsIFIP International Federation for Information Processingen_US
dc.subjectArtificial neural networken_US
dc.subjectSoftware projecten_US
dc.subjectArtificial neural network modelsen_US
dc.subjectAttribute selectionen_US
dc.subjectBackward eliminationen_US
dc.subjectComplex softwareen_US
dc.subjectConnection weightsen_US
dc.subjectCost driversen_US
dc.subjectGarson's algorithmen_US
dc.subjectInput dimensionsen_US
dc.subjectNetwork weightsen_US
dc.subjectNonlinear interactionsen_US
dc.subjectPrediction performanceen_US
dc.subjectSaliency measureen_US
dc.subjectSoftware cost estimationsen_US
dc.subjectSoftware development efforten_US
dc.subjectSoftware systemsen_US
dc.subjectAlgorithmsen_US
dc.subjectCostsen_US
dc.subjectEstimationen_US
dc.subjectProject managementen_US
dc.subjectSoftware designen_US
dc.subjectNeural networksen_US
dc.titleOn the problem of attribute selection for software cost estimation: Input backward elimination using artificial neural networksen_US
dc.typeConference Papersen_US
dc.collaborationUniversity of Cyprusen_US
dc.collaborationCyprus University of Technologyen_US
dc.subject.categoryElectrical Engineering - Electronic Engineering - Information Engineeringen_US
dc.countryCyprusen_US
dc.subject.fieldEngineering and Technologyen_US
dc.publicationPeer Revieweden_US
dc.relation.conferenceInternational Conference on Artificial Intelligence Applications and Innovationsen_US
dc.identifier.doi10.1007/978-3-642-16239-8_38en_US
dc.dept.handle123456789/134en
cut.common.academicyear2010-2011en_US
item.fulltextNo Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_c94f-
item.languageiso639-1en-
item.openairetypeconferenceObject-
item.grantfulltextnone-
item.cerifentitytypePublications-
crisitem.author.deptDepartment of Electrical Engineering, Computer Engineering and Informatics-
crisitem.author.facultyFaculty of Engineering and Technology-
crisitem.author.orcid0000-0001-7104-2097-
crisitem.author.parentorgFaculty of Engineering and Technology-
Appears in Collections:Δημοσιεύσεις σε συνέδρια/Conference papers
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