Please use this identifier to cite or link to this item:
http://hdl.handle.net/10603/422249
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.coverage.spatial | Electrical Engineering | |
dc.date.accessioned | 2022-12-07T10:31:47Z | - |
dc.date.available | 2022-12-07T10:31:47Z | - |
dc.identifier.uri | http://hdl.handle.net/10603/422249 | - |
dc.description.abstract | Abstract Available | |
dc.format.extent | ||
dc.language | English | |
dc.relation | TH-6588 | |
dc.rights | university | |
dc.title | Automated machine learning using particle swarm optimization | |
dc.title.alternative | Na | |
dc.creator.researcher | Singh, Pratibha | |
dc.subject.keyword | Engineering | |
dc.subject.keyword | Engineering and Technology | |
dc.subject.keyword | Engineering Electrical and Electronic | |
dc.description.note | ||
dc.contributor.guide | Chaudhury, Santanu and Panigrahi, Bijaya Ketan | |
dc.publisher.place | Delhi | |
dc.publisher.university | Indian Institute of Technology Delhi | |
dc.publisher.institution | Department of Electrical Engineering | |
dc.date.registered | ||
dc.date.completed | 2021 | |
dc.date.awarded | 2021 | |
dc.format.dimensions | ||
dc.format.accompanyingmaterial | DVD | |
dc.source.university | University | |
dc.type.degree | Ph.D. | |
Appears in Departments: | Department of Electrical Engineering |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
01_title.pdf | Attached File | 92.83 kB | Adobe PDF | View/Open |
02_prelim pages.pdf | 1.06 MB | Adobe PDF | View/Open | |
03_content.pdf | 390.41 kB | Adobe PDF | View/Open | |
04_abstract.pdf | 1.29 MB | Adobe PDF | View/Open | |
05_chapter 1.pdf | 4.23 MB | Adobe PDF | View/Open | |
06_chapter 2.pdf | 6.43 MB | Adobe PDF | View/Open | |
07_chapter 3.pdf | 9.36 MB | Adobe PDF | View/Open | |
08_chapter 4.pdf | 5.81 MB | Adobe PDF | View/Open | |
09_chapter 5.pdf | 7.06 MB | Adobe PDF | View/Open | |
10_chapter 6.pdf | 2.63 MB | Adobe PDF | View/Open | |
11_annexures.pdf | 9 MB | Adobe PDF | View/Open | |
80_recommendation.pdf | 2.67 MB | Adobe PDF | View/Open |
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