Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/428937
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dc.coverage.spatialLife Sciences
dc.date.accessioned2022-12-20T11:39:42Z-
dc.date.available2022-12-20T11:39:42Z-
dc.identifier.urihttp://hdl.handle.net/10603/428937-
dc.description.abstractAvailable
dc.format.extenti-vii, 1-161 p
dc.languageEnglish
dc.relation105
dc.rightsuniversity
dc.titleA data driven approach using arima and deep learning time series prediction for forecasting infectious diseases in mysuru karnataka
dc.title.alternative
dc.creator.researcherAbhinandithe K, Stavelin
dc.subject.keywordBiotechnology and Applied Microbiology
dc.subject.keywordInfectious Diseases, Time Series, Forecasting, NBR, GMDH, ARIMAX, LSTM, Prediction.
dc.subject.keywordLife Sciences
dc.subject.keywordMicrobiology
dc.description.notesummary p 152-153, References 155-161 p
dc.contributor.guideB, Madhu
dc.publisher.placeMysore
dc.publisher.universityJSS Academy of Higher Education and Research
dc.publisher.institutionLife Sciences
dc.date.registered2017
dc.date.completed2022
dc.date.awarded2022
dc.format.dimensions3
dc.format.accompanyingmaterialCD
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:Life Sciences

Files in This Item:
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01_title.pdfAttached File36.16 kBAdobe PDFView/Open
02_prelim pages.pdf5.96 MBAdobe PDFView/Open
03_contents.pdf1 MBAdobe PDFView/Open
04_abstract.pdf853.34 kBAdobe PDFView/Open
05_chapter 1.pdf1.2 MBAdobe PDFView/Open
06_chapter 2.pdf450.14 kBAdobe PDFView/Open
07_chapter 3.pdf456.67 kBAdobe PDFView/Open
08_chapter 4.pdf7.3 MBAdobe PDFView/Open
09_chapter 5.pdf20.86 kBAdobe PDFView/Open
10_chapter 6.pdf15.28 kBAdobe PDFView/Open
11_annexures.pdf466.4 kBAdobe PDFView/Open
80_recommendation.pdf440.69 kBAdobe PDFView/Open


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