Ehsan Harirchian
Guest Editor @Buildings Mdpi
Signup · Get unlimited contacts
WORK HISTORY
Guest Editor @Buildings Mdpi
Special Issue \"Building\'s Vulnerability Assessment against Natural Hazards by Using Modern Computational Techniques\"Recent destructive events around the world have illustrated the increasing importance of research on buildings, and specifically the assessment of their vulnerability against natural hazards. For instance, the classification and assessment of existing buildings’ earthquake resistance is a vital task that must be accomplished expeditiously and in a simple, economical, and accurate way before any earthquake actually takes place.Conducting a more detailed construction analysis and assembling comprehensive knowledge around a building’s geometry, features, and materials may lead to a very accurate non-linear seismic assessment. However, such an approach would entail unprecedented difficulties, considering that big data and an urban scale mitigation campaign exhibit a high dispersion level. Therefore, a fast and reliable method of identifying vulnerable buildings is required. Recently, numerous modern methods have been developed in soft computational techniques to deal with big data and consider non-linear relationships between parameters affecting buildings’ vulnerability against natural hazards such as earthquakes, floods, etc. Modern computational techniques (e.g, artificial neural networks, fuzzy logic) have shown vital efficiency and applicability in the vulnerability assessment of buildings against natural hazards.This special issue aims to invite ingenious authors and researchers to present their work and discover applied modern computing techniques and their utilization in evaluating buildings’ natural hazard safety, including but not limited to the following subtopics.
EDUCATION
Islamic Azad University
Bachelor’s Degree
Bauhaus-Universität Weimar
Master’s Degree
SKILLS
ABOUT EHSAN HARIRCHIAN
Interests-Soft computing techniques (Machine learning, Neural network and fuzzy…
This profile is compiled from publicly available professional sources. Unifers is not affiliated with or endorsed by LinkedIn. Request removal of this profile.