E
Ehsan Harirchian
Researcher at Bauhaus University, Weimar
Publications - 36
Citations - 539
Ehsan Harirchian is an academic researcher from Bauhaus University, Weimar. The author has contributed to research in topics: Computer science & Engineering. The author has an hindex of 10, co-authored 26 publications receiving 165 citations.
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A review on application of soft computing techniques for the rapid visual safety evaluation and damage classification of existing buildings
Ehsan Harirchian,Seyed Ehsan Aghakouchaki Hosseini,Kirti Jadhav,Vandana Kumari,Shahla Rasulzade,Ercan Işik,Muhamad Wasif,Tom Lahmer +7 more
TL;DR: There are structures still in service with a high seismic vulnerability, which proposes an urgent need for a screening system’s damageability grading system, and the necessity of developing a rapid, reliable, and computationally easy method of seismic vulnerability assessment, more commonly known as RVS.
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Developing a hierarchical type-2 fuzzy logic model to improve rapid evaluation of earthquake hazard safety of existing buildings
Ehsan Harirchian,Tom Lahmer +1 more
TL;DR: A novel framework for earthquake vulnerability assessment of buildings via Rapid Visual Screening (RVS) is proposed using type-2 fuzzy, which can handle vagueness sufficiently besides being a quick and affordable method.
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Damage and performance evaluation of masonry buildings constructed in 1970s during the 2019 Albania earthquakes
Hüseyin Bilgin,Neritan Shkodrani,Marjo Hysenlliu,Hayri Baytan Ozmen,Ercan Işik,Ehsan Harirchian +5 more
TL;DR: In this article, the seismic response of masonry buildings damaged during the 2019 Mw 6.4 earthquake was investigated, and four important typologies were selected to draw general conclusions from the performance analysis and damage assessment.
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Strategies for Adopting Building Information Modeling (BIM) in Sustainable Building Projects—A Case of Malaysia
TL;DR: In this paper, a systematic literature review was performed to classify the strategies to accomplish this aim, followed by a questionnaire survey of 129 construction project stakeholders, which revealed that workshops, lectures, and conference events are used to enhance public awareness and better information on the costs and benefits of sustainable materials.
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Earthquake Hazard Safety Assessment of Existing Buildings Using Optimized Multi-Layer Perceptron Neural Network
TL;DR: The results demonstrate the feasibility and effectiveness of the selected ANN approach to classify concrete structural damage that can be used as a preliminary assessment technique to identify vulnerable buildings in disaster risk-management programs.