Intelligent Learning in Assessing the Effects of Earthquakes on Structural Behavior

Document Type : Research Paper

Authors

1 B.Sc., Department of Civil Engineering, Gorgan Faculty of Engineering, Golestan University, Gorgan, Iran

2 Department of Civil Engineering, Gorgan Faculty of Engineering, Golestan University, Gorgan, Iran

3 Department of Civil Engineering, Faculty of Engineering Golestan University

Abstract

Machine learning (ML) has undergone significant changes in recent years and the strengthening of the role of data science in its various forms evolved rapidly. Compared to traditional approaches, ML facilitates the benefits of dealing with complex problems, providing computational efficiency, dissemination, treatment of uncertainty, and decision making. Also, the growth of ML has led to significant advances not only in mainstream artificial intelligence (AI) research but also in other fields of science and engineering, such as materials science, bioengineering, construction management, and transportation engineering. Due to the unknown seismic dimensions and seismic behavior of the structure, this paper examines the progress and challenges of ML implementation in this area. Studies show that the use of ML in three areas of earthquake risk assessment, structural damage risk assessment before and after the earthquake and control of seismic behavior of the structure with the aim of reducing the effects of earthquakes can be considered.

Keywords

References

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New Approaches in Civil Engineering
Volume 5, Issue 2
September 2021
Pages 46-61

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