Enhancing credit risk prediction with hybrid deep learning and sand cat swarm feature selection.
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| Title: | Enhancing credit risk prediction with hybrid deep learning and sand cat swarm feature selection. |
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| Authors: | Ramesh, R.1, rameshau04@gmail.com, Jeyakarthic, M.1 |
| Source: | Multimedia Tools & Applications; Jun2024, Vol. 83 Issue 21, p60243-60263, 21p |
| Database: | Applied Science & Technology Source |
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| FullText | Links: – Type: pdflink Text: Availability: 1 |
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| Header | DbId: aci DbLabel: Applied Science & Technology Source An: 177623545 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Enhancing credit risk prediction with hybrid deep learning and sand cat swarm feature selection. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AU" term="%22Ramesh%2C+R%2E%22">Ramesh, R.</searchLink><relatesTo>1</relatesTo>, <i>rameshau04@gmail.com</i><br /><searchLink fieldCode="AU" term="%22Jeyakarthic%2C+M%2E%22">Jeyakarthic, M.</searchLink><relatesTo>1</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Multimedia+Tools+%26+Applications%22">Multimedia Tools & Applications</searchLink>; Jun2024, Vol. 83 Issue 21, p60243-60263, 21p |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=177623545 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s11042-023-17974-3 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 21 StartPage: 60243 Titles: – TitleFull: Enhancing credit risk prediction with hybrid deep learning and sand cat swarm feature selection. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Ramesh, R. – PersonEntity: Name: NameFull: Jeyakarthic, M. IsPartOfRelationships: – BibEntity: Dates: – D: 21 M: 06 Text: Jun2024 Type: published Y: 2024 Identifiers: – Type: issn-print Value: 13807501 Numbering: – Type: volume Value: 83 – Type: issue Value: 21 Titles: – TitleFull: Multimedia Tools & Applications Type: main |
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