Mimar Sinan Güzel Sanatlar Üniversitesi Açık Bilim, Sanat Arşivi

Açık Bilim, Sanat Arşivi, Mimar Sinan Güzel Sanatlar Üniversitesi tarafından doğrudan ve dolaylı olarak yayınlanan; kitap, makale, tez, bildiri, rapor gibi tüm akademik kaynakları uluslararası standartlarda dijital ortamda depolar, Üniversitenin akademik performansını izlemeye aracılık eder, kaynakları uzun süreli saklar ve yayınların etkisini artırmak için telif haklarına uygun olarak Açık Erişime sunar.

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dc.contributor.authorAydın, Yaren
dc.contributor.authorBekdaş, Gebrail
dc.contributor.authorNigdeli, Sinan Melih
dc.contributor.authorIşıkdağ, Ümit
dc.contributor.authorGeem, Zong Woo
dc.date.accessioned2025-01-09T20:03:32Z
dc.date.available2025-01-09T20:03:32Z
dc.date.issued2023
dc.identifier.issn2198-4182
dc.identifier.urihttps://doi.org/10.1007/978-3-031-34728-3_12
dc.identifier.urihttps://hdl.handle.net/20.500.14124/7544
dc.description.abstractMachine learning has become a popular science in recent years, as it produces concrete and fast solutions to solve many problems. The rapidly increasing world population and the developments in technology have caused large greenhouse gas emissions. The harmful effects of carbon dioxide emissions from cement in concrete on climate change and global warming are quite remarkable. In this study, the most commonly used machine learning (ML) models in the literature were used for CO2 minimization of reinforced concrete columns. Harmony search was employed to find the optimum dataset for machine learning. The performances of these algorithms were compared and the best algorithm was tried to be found. As a result of all, it is observed that Multilayer Perceptron (MLP) has higher performance than other algorithms. The R2 of the MLP is 0.999. According to this result, it was observed that MLP is the most successful ML model in the design of eco-friendly reinforced concrete columns. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.en_US
dc.language.isoengen_US
dc.publisherSpringer Science and Business Media Deutschland GmbHen_US
dc.relation.ispartofStudies in Systems, Decision and Controlen_US
dc.rightsKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.subjectCO<sub>2</sub> emissionen_US
dc.subjectColumnsen_US
dc.subjectHarmony searchen_US
dc.subjectMachine learningen_US
dc.subjectReinforced concreteen_US
dc.titleComparison of Multilayer Perceptron and Other Methods for Prediction of Sustainable Optimum Design of Reinforced Concrete Columnsen_US
dc.typebookParten_US
dc.departmentMimar Sinan Güzel Sanatlar Üniversitesien_US
dc.identifier.doi10.1007/978-3-031-34728-3_12
dc.identifier.volume480en_US
dc.identifier.startpage235en_US
dc.identifier.endpage263en_US
dc.relation.publicationcategoryKitap Bölümü - Uluslararasıen_US
dc.identifier.scopus2-s2.0-85194820774en_US
dc.identifier.scopusqualityQ2
dc.indekslendigikaynakScopus
dc.snmzKA_20250105


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