Çankaya GCRIS Standart veritabanının içerik oluşturulması ve kurulumu Research Ecosystems (https://www.researchecosystems.com) tarafından devam etmektedir. Bu süreçte gördüğünüz verilerde eksikler olabilir.
 

Artificial intelligence applications in earthquake resistant architectural design: Determination of irregular structural systems with deep learning and ImageAI method

dc.contributor.authorBingöl, Kaan
dc.contributor.authorEr Akan, Aslı
dc.contributor.authorÖmercioğlu, Hilal Tuğba
dc.contributor.authorEr, Arzu
dc.contributor.authorID154406tr_TR
dc.date.accessioned2021-06-09T12:22:43Z
dc.date.available2021-06-09T12:22:43Z
dc.date.issued2020
dc.departmentÇankaya Üniversitesi, Mimarlık Fakültesi, Mimarlık Bölümüen_US
dc.description.abstractAlthough the architectural design process is carried out with the collaboration of experts who are experienced in many different areas from the main preferences to the detailing stage, the major decisions such as plan organization, mass design etc. are taken by the architect. Computer Aided Design (CAD) programs are generally effective after the major decisions of the design are taken. For this reason, it is common for the main decisions, taken during the design process, to be changed during the analysis of the structural system. In order to prevent this, in the early stages of architectural design, earthquake system awareness and structural system design should be included as an design input; as, the failure of the structural system which did not considered well in the architectural design phase leads to unexpected revisions in the implementation project phase and thus leads to serious losses in both time and cost. The aim of this study is to create an Irregularity Control Assistant (IC Assitant) that can provide architects general information about the appropriateness of structural system decisions to earthquake regulations in the early stages of design process by using the deep learning and image processing methods. In this way, correct decisions will be made in the early stages of the design and unexpected revisions that may occur during the implementation project phase will be prevented.en_US
dc.identifier.citationBingöl, Kaan...at all (2020). "Artificial intelligence applications in earthquake resistant architectural design: Determination of irregular structural systems with deep learning and ImageAI method", Gazi University Journal of Engineering and Architecture, Vol. 35, No. 4, pp. 2197-2209.en_US
dc.identifier.endpage2209en_US
dc.identifier.issn1300-1884
dc.identifier.issn1304-4915
dc.identifier.issue4en_US
dc.identifier.startpage2197en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12416/4746
dc.identifier.volume35en_US
dc.language.isoenen_US
dc.relation.ispartofGazi University Journal of Engineering and Architectureen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectEarthquake Codeen_US
dc.subjectDeep Learningen_US
dc.subjectImageaien_US
dc.subjectPythonen_US
dc.subjectArtificial Intelligenceen_US
dc.titleArtificial intelligence applications in earthquake resistant architectural design: Determination of irregular structural systems with deep learning and ImageAI methodtr_TR
dc.titleArtificial Intelligence Applications in Earthquake Resistant Architectural Design: Determination of Irregular Structural Systems With Deep Learning and Imageai Methoden_US
dc.typeArticleen_US
dspace.entity.typePublication

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