1. Shodhganga@INFLIBNET
  2. National Institute of Technology Raipur
  3. Electrical Engineering
Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/456523
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DC FieldValueLanguage
dc.coverage.spatial
dc.date.accessioned2023-02-06T10:59:02Z-
dc.date.available2023-02-06T10:59:02Z-
dc.identifier.urihttp://hdl.handle.net/10603/456523-
dc.description.abstractnewlineAttached
dc.format.extentXXII, 165
dc.languageEnglish
dc.relation
dc.rightsuniversity
dc.titleForecasting of solar power generation using optimally tuned extreme learning machine
dc.title.alternative
dc.creator.researcherSahu, Raj Kumar
dc.subject.keywordArtificial Intelligence
dc.subject.keywordElectrical Engineering
dc.subject.keywordEngineering
dc.subject.keywordEngineering and Technology
dc.subject.keywordForecasting
dc.subject.keywordOptimization
dc.description.note
dc.contributor.guideShaw, Binod
dc.publisher.placeRaipur
dc.publisher.universityNational Institute of Technology Raipur
dc.publisher.institutionElectrical Engineering
dc.date.registered2016
dc.date.completed2021
dc.date.awarded2022
dc.format.dimensions
dc.format.accompanyingmaterialNone
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:Electrical Engineering

Files in This Item:
File Description SizeFormat 
01_tiitle.pdfAttached File405.75 kBAdobe PDFView/Open
02_preliminary page.pdf880.29 kBAdobe PDFView/Open
03_content.pdf296.31 kBAdobe PDFView/Open
04_abstract.pdf285.94 kBAdobe PDFView/Open
05_chapter 1.pdf1.23 MBAdobe PDFView/Open
06_chapter 2.pdf1.55 MBAdobe PDFView/Open
07_chapter 3.pdf3.09 MBAdobe PDFView/Open
08_chapter 4.pdf5.71 MBAdobe PDFView/Open
09_chapter 5.pdf3.23 MBAdobe PDFView/Open
10_chapter 6.pdf1.15 MBAdobe PDFView/Open
11_annextures.pdf933.44 kBAdobe PDFView/Open
80_recommendation.pdf474.71 kBAdobe PDFView/Open
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