Comprehensive review of AI and ML tools for earthquake damage assessment and retrofitting strategies

IF 2.7 4区地球科学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Earth Science Informatics Pub Date : 2024-08-06 DOI:10.1007/s12145-024-01431-2

P. K. S. Bhadauria

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引用次数: 0

Abstract

This comprehensive review paper examines the integration of Artificial Intelligence (AI) and Machine Learning (ML) tools in earthquake engineering, specifically focusing on damage assessment and retrofitting strategies. The paper begins with an introduction to AI and its significance in structural engineering, highlighting the need for advanced methodologies to address seismic challenges. A detailed review of recent applications of ML, Pattern Recognition (PR), and Deep Learning (DL) in earthquake engineering is provided, showcasing their capabilities in surpassing the limitations of traditional models. The advantages of employing these algorithmic methods in damage assessment, retrofitting designs, risk prediction, and structural optimization are discussed extensively. Furthermore, the paper identifies potential research avenues and emerging trends in AI/ML applications for earthquake resilience, while also addressing the challenges and limitations associated with these technologies. Overall, this review paper offers a comprehensive overview of the current state-of-the-art in AI and ML tools for earthquake damage assessment and retrofitting strategies, paving the way for future advancements in seismic resilience engineering.

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全面审查用于地震破坏评估和改造战略的人工智能和 ML 工具

这篇综合综述论文探讨了人工智能（AI）和机器学习（ML）工具在地震工程中的应用，尤其关注破坏评估和改造策略。论文首先介绍了人工智能及其在结构工程中的意义，强调了采用先进方法应对地震挑战的必要性。本文详细回顾了人工智能、模式识别（PR）和深度学习（DL）在地震工程中的最新应用，展示了它们超越传统模型局限的能力。论文广泛讨论了在损害评估、改造设计、风险预测和结构优化中采用这些算法方法的优势。此外，本文还指出了人工智能/ML 应用于抗震方面的潜在研究途径和新兴趋势，同时还探讨了与这些技术相关的挑战和局限性。总之，本综述论文全面概述了当前用于地震破坏评估和改造策略的人工智能和 ML 工具的最先进水平，为未来抗震工程的进步铺平了道路。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Earth Science Informatics COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-GEOSCIENCES, MULTIDISCIPLINARY

CiteScore

4.60

自引率

3.60%

发文量

157

审稿时长

4.3 months

期刊介绍： The Earth Science Informatics [ESIN] journal aims at rapid publication of high-quality, current, cutting-edge, and provocative scientific work in the area of Earth Science Informatics as it relates to Earth systems science and space science. This includes articles on the application of formal and computational methods, computational Earth science, spatial and temporal analyses, and all aspects of computer applications to the acquisition, storage, processing, interchange, and visualization of data and information about the materials, properties, processes, features, and phenomena that occur at all scales and locations in the Earth system’s five components (atmosphere, hydrosphere, geosphere, biosphere, cryosphere) and in space (see "About this journal" for more detail). The quarterly journal publishes research, methodology, and software articles, as well as editorials, comments, and book and software reviews. Review articles of relevant findings, topics, and methodologies are also considered.