1. Shodhganga@INFLIBNET
  2. GIET University, Gunupur
  3. Computer Science and Engineering
Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/515468
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DC FieldValueLanguage
dc.coverage.spatial
dc.date.accessioned2023-10-03T09:03:06Z-
dc.date.available2023-10-03T09:03:06Z-
dc.identifier.urihttp://hdl.handle.net/10603/515468-
dc.description.abstractnewline
dc.format.extent171p.
dc.languageEnglish
dc.relation
dc.rightsuniversity
dc.titlePrediction and analysis of biological data using learning models and fuzzy rule mining
dc.title.alternative
dc.creator.researcherMahanty, Chandrakanta
dc.subject.keywordComputer Science
dc.subject.keywordComputer Science Artificial Intelligence
dc.subject.keywordEngineering and Technology
dc.description.noteThe thesis includes various proposed methodologies, algorithms to detect and predict COVID-19 positive cases. Various non-linear growth models, transfer learning mechanisms, fusions of transfer learning with fuzzy ensemble models, and fuzzy inference mechanisms are presented with results. It also discusses sexual and mental well-being during and after COVID-19.
dc.contributor.guideKumar, Raghvendra
dc.publisher.placeGunupur
dc.publisher.universityGIET University, Gunupur
dc.publisher.institutionComputer Science and Engineering
dc.date.registered
dc.date.completed2023
dc.date.awarded2023
dc.format.dimensions
dc.format.accompanyingmaterialDVD
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:Computer Science and Engineering

Files in This Item:
File Description SizeFormat 
01_title.pdfAttached File318.41 kBAdobe PDFView/Open
02_prelim pages.pdf779.57 kBAdobe PDFView/Open
03_table of contents.pdf319 kBAdobe PDFView/Open
04_abstract.pdf210.36 kBAdobe PDFView/Open
05_chapter 1.pdf214.01 kBAdobe PDFView/Open
06_chapter 2.pdf144.77 kBAdobe PDFView/Open
07_chapter 3.pdf893.32 kBAdobe PDFView/Open
08_chapter 4.pdf198.79 kBAdobe PDFView/Open
09_chapter 5.pdf523.67 kBAdobe PDFView/Open
10_chapter 6.pdf614.38 kBAdobe PDFView/Open
11_chapter 7.pdf287.66 kBAdobe PDFView/Open
12_chapter 8.pdf7.61 kBAdobe PDFView/Open
13_annexure.pdf966.77 kBAdobe PDFView/Open
80_recommendation.pdf7.61 kBAdobe PDFView/Open
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