Long Short-Term Memory Neural Networks for Modeling Dynamical Processes and Predictive Control: A Hybrid Physics-Informed Approach.
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| Title: | Long Short-Term Memory Neural Networks for Modeling Dynamical Processes and Predictive Control: A Hybrid Physics-Informed Approach. |
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| Authors: | Zarzycki, Krzysztof1 (AUTHOR) krzysztof.zarzycki@pw.edu.pl, Ławryńczuk, Maciej1 (AUTHOR) |
| Source: | Sensors (14248220). Nov2023, Vol. 23 Issue 21, p8898. 27p. |
| Database: | Academic Search Ultimate |
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| FullText | Links: – Type: pdflink Text: Availability: 1 |
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| Header | DbId: asn DbLabel: Academic Search Ultimate An: 173565546 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Long Short-Term Memory Neural Networks for Modeling Dynamical Processes and Predictive Control: A Hybrid Physics-Informed Approach. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Zarzycki%2C+Krzysztof%22">Zarzycki, Krzysztof</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> krzysztof.zarzycki@pw.edu.pl</i><br /><searchLink fieldCode="AR" term="%22Ławryńczuk%2C+Maciej%22">Ławryńczuk, Maciej</searchLink><relatesTo>1</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Sensors+%2814248220%29%22">Sensors (14248220)</searchLink>. Nov2023, Vol. 23 Issue 21, p8898. 27p. |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asn&AN=173565546 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.3390/s23218898 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 27 StartPage: 8898 Titles: – TitleFull: Long Short-Term Memory Neural Networks for Modeling Dynamical Processes and Predictive Control: A Hybrid Physics-Informed Approach. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Zarzycki, Krzysztof – PersonEntity: Name: NameFull: Ławryńczuk, Maciej IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 11 Text: Nov2023 Type: published Y: 2023 Identifiers: – Type: issn-print Value: 14248220 Numbering: – Type: volume Value: 23 – Type: issue Value: 21 Titles: – TitleFull: Sensors (14248220) Type: main |
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