1. Ktisis Cyprus University of Technology
  2. Cyprus University of Technology (Research Output)
  3. Δημοσιεύσεις σε συνέδρια /Conference papers or poster or presentation
Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/13812
DC FieldValueLanguage
dc.contributor.authorKoutsimpelas, Alexandros-
dc.contributor.authorAndreou, Andreas S.-
dc.date.accessioned2019-05-27T05:51:29Z-
dc.date.available2019-05-27T05:51:29Z-
dc.date.issued2006-06-
dc.identifier.citationArtificial Intelligence Applications and Innovations. AIAI 2006. IFIP International Federation for Information Processing, vol 204, pp. 524-532en_US
dc.identifier.isbn978-0-387-34224-5-
dc.description.abstractSoftware failure and software reliability are strongly related concepts. Introducing a model that would perform successful failure prediction could provide the means for achieving higher software reliability and quality. In this context, we have employed artificial neural networks and genetic algorithms to investigate whether software failure can be accurately modeled and forecasted based on empirical data of real systems. © 2006 International Federation for Information Processing.en_US
dc.formatpdfen_US
dc.language.isoenen_US
dc.rights© International Federation for Information Processingen_US
dc.subjectEvolutionary algorithmsen_US
dc.subjectClassification (of information)en_US
dc.subjectNeural networksen_US
dc.titleInvestigating the predictability of empirical software failure data with artificial neural networks and hybrid modelsen_US
dc.typeConference Papersen_US
dc.collaborationUniversity of Cyprusen_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.doi10.1007/0-387-34224-9_61en_US
dc.identifier.scopus2-s2.0-33749145872en
dc.identifier.urlhttps://api.elsevier.com/content/abstract/scopus_id/33749145872en
dc.contributor.orcid#NODATA#en
dc.contributor.orcid#NODATA#en
dc.relation.volume204en
cut.common.academicyear2005-2006en_US
item.fulltextNo Fulltext-
item.cerifentitytypePublications-
item.grantfulltextnone-
item.openairecristypehttp://purl.org/coar/resource_type/c_c94f-
item.openairetypeconferenceObject-
item.languageiso639-1en-
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 or poster or presentation
CORE Recommender
Show simple item record

Page view(s) 50

297
Last Week
1
Last month
10
checked on May 13, 2024

Google ScholarTM

Check

Altmetric


Items in KTISIS are protected by copyright, with all rights reserved, unless otherwise indicated.