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dc.contributor.advisorBremdal, Bernt Arild
dc.contributor.authorJansson, Andreas Dyrøy
dc.date.accessioned2017-08-24T12:43:47Z
dc.date.available2017-08-24T12:43:47Z
dc.date.issued2017-06-13
dc.description.abstractThis thesis discusses the process of implementing and testing of a creative web element design system using a combination of genetic algorithms and K-nearest neighbor classification. Classification will be used as a learning mechanism to give the system the ability to absorb quality measures in regards to visual aesthetics, and utilize this knowledge to evaluate generated designs. In addition, some basic concepts regarding web design will be covered, along with an introduction to artificial intelligence-based design. The results of the implementation will be discussed and compared to related state-of-the-art systems.en_US
dc.identifier.urihttps://hdl.handle.net/10037/11368
dc.language.isoengen_US
dc.publisherUiT Norges arktiske universiteten_US
dc.publisherUiT The Arctic University of Norwayen_US
dc.rights.accessRightsopenAccessen_US
dc.rights.holderCopyright 2017 The Author(s)
dc.subject.courseIDSHO6264
dc.subjectVDP::Teknologi: 500::Informasjons- og kommunikasjonsteknologi: 550en_US
dc.subjectVDP::Technology: 500::Information and communication technology: 550en_US
dc.subjectGenetic algorithmen_US
dc.subjectclassificationen_US
dc.subjectK-nearest neighboren_US
dc.subjectweb designen_US
dc.titleGenetic algorithms (GA) for adaptable designen_US
dc.typeMaster thesisen_US
dc.typeMastergradsoppgaveen_US


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