Document Type

Article

Version Deposited

Published Version

Publication Date

4-2020

Publication Title

Journal of Soft Computing in Civil Engineering

DOI

10.22115/SCCE.2020.223322.1186

Abstract

Seismic vulnerability means the inability of historical and monumental buildings to withstand the effects of seismic forces. This article presents a classification model to specify the damage state of the Reinforced Concrete (RC) frames based on a collection of datasets from the damaged buildings in Bingol earthquake of Turkey for use in the learning process of the algorithm. The proposed model uses two classifiers including the redundancy and also the construction quality of the buildings to estimate the class of damage from four categories including none, light, moderate and severe. The available database of the considered earthquake includes the information of 27 damaged RC buildings which are published in the literature. The model provided a simple structure for engineers to predict the class without complex calculations in which it needs a few steps to determine the class of damage for RC frames. The results show that the presented model can estimate the class of each input vector with an acceptable error.

Comments

Journal of Soft Computing in Civil Engineering is licensed under a Creative Commons Attribution 4.0 International License.

Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

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