气候变化领域集成服务门户(CCPortal): Exploring the Potential for Incorporating Artificial Intelligence in Highway Resilience to Climate Change

CCPortal

DOI	10.1177/03611981241253610
	Exploring the Potential for Incorporating Artificial Intelligence in Highway Resilience to Climate Change
	Mohamed, Khalid; Shen, Jia-Dzwan (Jerry)
发表日期	2024
ISSN	0361-1981
EISSN	2169-4052
英文摘要	Highway infrastructure needs to be able to withstand, recover quickly, and adapt to the extreme conditions and loads associated with climate change and other natural hazards. Investigation of new analysis methods of the different types of data for improving transportation resilience is critical. The highway owners are challenged with managing the highway geotechnical features and structures to achieve the adaptive capability. The optimization of the investment requires quantification of the changing hazards and correlation to infrastructure performance. The use of new and broader data sources and artificial intelligence (AI) and machine learning (ML) opens a door to more efficient development of necessary models with many potentially relevant variables and a more adaptive updating process. Climate tools developed by the Federal Highway Administration could be integrated with or enhanced using AI/ML modules trained using properly selected data. The improvement of infrastructure resilience also depends on adequate evaluation of the probability of various damage levels from extreme events. The application of AI/ML on a broader data source will enable data-driven probabilistic damage modeling approaches that are often not feasible using traditional regression processes. This paper discusses from a user's point of view several potential applications that could take advantage of AI/ML techniques and big data availability, including geotechnical asset management, geohazard programs, and probabilistic damage evaluation. Challenges in current practice are analyzed and connected to the need for a new approach. The anticipated applicable areas are offered to the AI/ML professionals to consider for further studies.
英文关键词	geohazards; artificial intelligence; machine learning; geotechnical asset management; climate change; resilience; fragility
语种	英语
WOS研究方向	Engineering ; Transportation
WOS类目	Engineering, Civil ; Transportation ; Transportation Science & Technology
WOS记录号	WOS:001236461700001
来源期刊	TRANSPORTATION RESEARCH RECORD
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/309906
推荐引用方式 GB/T 7714	Mohamed, Khalid,Shen, Jia-Dzwan . Exploring the Potential for Incorporating Artificial Intelligence in Highway Resilience to Climate Change[J],2024.
APA	Mohamed, Khalid,&Shen, Jia-Dzwan .(2024).Exploring the Potential for Incorporating Artificial Intelligence in Highway Resilience to Climate Change.TRANSPORTATION RESEARCH RECORD.
MLA	Mohamed, Khalid,et al."Exploring the Potential for Incorporating Artificial Intelligence in Highway Resilience to Climate Change".TRANSPORTATION RESEARCH RECORD (2024).