Predictive Energy and Exergy Assessment of Photovoltaic Systems Under Dynamic Environmental Conditions Using Machine Learning.
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| Title: | Predictive Energy and Exergy Assessment of Photovoltaic Systems Under Dynamic Environmental Conditions Using Machine Learning. |
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| Authors: | Şahin, Gökhan1,2, Akin, Erdal2,3,4,5,6, erdal.akin@mau.se |
| Source: | Applied Sciences (2076-3417); May2026, Vol. 16 Issue 10, p5049, 25p |
| 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: 194142443 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Predictive Energy and Exergy Assessment of Photovoltaic Systems Under Dynamic Environmental Conditions Using Machine Learning. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AU" term="%22Şahin%2C+Gökhan%22">Şahin, Gökhan</searchLink><relatesTo>1,2</relatesTo><br /><searchLink fieldCode="AU" term="%22Akin%2C+Erdal%22">Akin, Erdal</searchLink><relatesTo>2,3,4,5,6</relatesTo>, <i>erdal.akin@mau.se</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Applied+Sciences+%282076-3417%29%22">Applied Sciences (2076-3417)</searchLink>; May2026, Vol. 16 Issue 10, p5049, 25p |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=194142443 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.3390/app16105049 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 25 StartPage: 5049 Titles: – TitleFull: Predictive Energy and Exergy Assessment of Photovoltaic Systems Under Dynamic Environmental Conditions Using Machine Learning. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Şahin, Gökhan – PersonEntity: Name: NameFull: Akin, Erdal IsPartOfRelationships: – BibEntity: Dates: – D: 15 M: 05 Text: May2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 20763417 Numbering: – Type: volume Value: 16 – Type: issue Value: 10 Titles: – TitleFull: Applied Sciences (2076-3417) Type: main |
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