Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/11832
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dc.contributor.authorEjder, A.B.-
dc.contributor.authorUlucak, O.-
dc.contributor.authorAyli, E.-
dc.contributor.authorCelebioglu, K.-
dc.contributor.authorAradag, S.-
dc.date.accessioned2024-10-10T15:47:49Z-
dc.date.available2024-10-10T15:47:49Z-
dc.date.issued2024-
dc.identifier.issn2578-5486-
dc.identifier.urihttps://hdl.handle.net/20.500.11851/11832-
dc.description9th International Symposium on Advances in Computational Heat Transfer, CHT 2024 -- 26 May 2024 through 30 May 2024 -- Istanbul -- 317889en_US
dc.description.abstractIn the study, a sequence-to-one regression methodology utilizing the predictive capabilities of the Long Short-Term Memory (LSTM) algorithm was employed to provide forecasts of flow rate values in the future time periods based on the two-year discharge data of Akbas HEPP Irrigation Canal. Thus, the aim is to evaluate the algorithm's forecasting ability for different timeframes beyond the existing dataset. Predictions for the future working conditions were sought by comparing the results of the pelton-type turbine, designed using traditional methods based on the current dataset, with the anticipated outcomes. Additionally, a study was conducted to optimize the performance of the LSTM design. After selecting the appropriate architecture, it was observed that the Long Short-Term Memory (LSTM) architecture, used for flow prediction in irrigation systems, achieved approximately 0.96, 0.92, and 0.90 R2 values, confirming its effectiveness in prediction tasks. LSTM models were trained multiple times, consistently demonstrating strong performance with diverse values for different prediction horizons. © 2024, Begell House Inc. All rights reserved.en_US
dc.description.sponsorshipDenizli Metropolitan Municipality Water and Sewerage Administration General Directorate; Türkiye Bilimsel ve Teknolojik Araştırma Kurumu, TÜBİTAK; ETU Hydro Laboratory; TOBB University of Economics and Technology Hydro Energy Research Center; Turkish Ministry of Developmenten_US
dc.language.isoenen_US
dc.publisherBegell House Inc.en_US
dc.relation.ispartofInternational Symposium on Advances in Computational Heat Transferen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.titleA Future Demand Prediction Based Approach for the Design of Pelton Turbines on Irrigation Channelsen_US
dc.typeConference Objecten_US
dc.departmentTOBB ETÜen_US
dc.identifier.volume2024en_US
dc.identifier.startpage315en_US
dc.identifier.endpage330en_US
dc.identifier.scopus2-s2.0-85204067897en_US
dc.institutionauthor-
dc.authorscopusid59329248500-
dc.authorscopusid57220077206-
dc.authorscopusid55371892800-
dc.authorscopusid37661052300-
dc.authorscopusid11440423900-
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
item.openairetypeConference Object-
item.languageiso639-1en-
item.grantfulltextnone-
item.fulltextNo Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
crisitem.author.dept13. TOBB ETÜ HIDRO Water Turbine Design and Test Center-
Appears in Collections:Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
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