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dc.contributor.advisorSurapong Auwatanamongkol, advisorth
dc.contributor.authorNalerk Sriwachirawatth
dc.date.accessioned2014-05-05T08:54:58Z
dc.date.available2014-05-05T08:54:58Z
dc.date.issued2006th
dc.identifier.urihttp://repository.nida.ac.th/handle/662723737/422th
dc.descriptionThesis (M.S. (Computer Science))--National Institute of Development Administration, 2006.th
dc.description.provenanceMade available in DSpace on 2014-05-05T08:54:58Z (GMT). No. of bitstreams: 2 nida-ths-b150085.pdf: 17612338 bytes, checksum: ba162688858564c4f990911717df5a44 (MD5) nida-ths-b150085ab.pdf: 59915 bytes, checksum: 562eed2aff855407438c0102e3e358cc (MD5) Previous issue date: 2006th
dc.format.extentxiii, 117 leaves ; 30 cm.th
dc.format.mimetypeapplication/pdfth
dc.language.isoength
dc.publisherNational Institute of Development Administrationth
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.th
dc.subject.lccQA 76.623 N147 2006th
dc.subject.otherGenetic algorithmsth
dc.subject.otherGenetic programming (Computer science)th
dc.subject.otherArtificial intelligenceth
dc.titleOn approximating K-Most probable explanations of Bayesian networks using genetic algorithmsth
dc.typeTextth
mods.genreThesisth
mods.physicalLocationNational Institute of Development Administration. Library and Information Centerth
thesis.degree.nameMaster of Scienceth
thesis.degree.levelMaster'sth
thesis.degree.disciplineComputer Scienceth
thesis.degree.grantorNational Institute of Development Administrationth
thesis.degree.departmentSchool of Applied Statisticsth


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