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Artificial Intelligence Applications in Earthquake Resistant Architectural Design: Determination of Irregular Structural Systems With Deep Learning and Imageai Method

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Date

2020

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Gazi Univ, Fac Engineering Architecture

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Abstract

Although 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.

Description

Er Akan, Asli/0000-0001-5362-8625; Ormecioglu, Hilal Tugba/0000-0002-0662-4178

Keywords

Earthquake Code, Deep Learning, Imageai, Python, Artificial Intelligence

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Citation

Bingöl, Kaan...et al (2020). "Artificial intelligence applications in earthquake resistant architectural design: Determination of irregular structural systems with deep learning and ImageAI method", Journal of the Faculty of Engineering and Architecture of Gazi University, Vol. 35, No. 4, pp. 2197-2209.

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Q4

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Q3
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11

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35

Issue

4

Start Page

2197

End Page

2209
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CrossRef : 8

Scopus : 16

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Mendeley Readers : 71

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