Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/92371
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dc.coverage.spatialComputer Science
dc.date.accessioned2016-05-26T09:50:48Z-
dc.date.available2016-05-26T09:50:48Z-
dc.identifier.urihttp://hdl.handle.net/10603/92371-
dc.description.abstractSuccess of any software organization depends on total customer satisfaction which in turn depends on the development of quality software Software Engineering methodology enables the production of quality software newline newline
dc.format.extent145 p.
dc.languageEnglish
dc.relation
dc.rightsuniversity
dc.titleAn enhanced approach for prediction of software project success using fuzzy cmeans genetic algorithm and random forest in software industry
dc.title.alternative
dc.creator.researcherPushpavathi T P
dc.subject.keywordGenetic Algorithm
dc.subject.keywordSoftware Engineering
dc.description.noteBibliography 114 - 124 p.
dc.contributor.guideRamaswamy V
dc.publisher.placeBengaluru
dc.publisher.universityJain University
dc.publisher.institutionDepartment of Computer Science Engineering
dc.date.registered05/04/2012
dc.date.completed16/01/2016
dc.date.awarded21/03/2016
dc.format.dimensions
dc.format.accompanyingmaterialNone
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:Department of Computer Science Engineering

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01_title pages.pdfAttached File11.51 kBAdobe PDFView/Open
02_certificate.pdf294.51 kBAdobe PDFView/Open
03_declaration.pdf415.5 kBAdobe PDFView/Open
04_acknowledgement.pdf12.89 kBAdobe PDFView/Open
05_abstract.pdf13.36 kBAdobe PDFView/Open
06_contents.pdf22.52 kBAdobe PDFView/Open
07_chapter 1.pdf90.91 kBAdobe PDFView/Open
08_chapter 2.pdf115.66 kBAdobe PDFView/Open
09_chapter 3.pdf1.23 MBAdobe PDFView/Open
10_chapter 4.pdf900.8 kBAdobe PDFView/Open
11_chapter 5.pdf973.46 kBAdobe PDFView/Open
12_chapter 6.pdf869.52 kBAdobe PDFView/Open
13_chapter 7.pdf44.5 kBAdobe PDFView/Open
14_bibliography.pdf108.98 kBAdobe PDFView/Open


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