气候变化领域集成服务门户(CCPortal): Modeling the economic impact of incoming tropical cyclones using machine learning

CCPortal

DOI	10.1007/s11069-021-04955-8
	Modeling the economic impact of incoming tropical cyclones using machine learning
	Wendler-Bosco V.; Nicholson C.
发表日期	2021
ISSN	0921030X
英文摘要	Hurricanes and tropical storms are natural hazards with the capacity to devastate coastal regions. Understanding this catastrophic potential is critical to support informed decision-making at local, state, and federal levels. The primary objective of this research is to use machine learning to rigorously explore and quantify the relationship of tropical cyclone characteristics to their destructive outcomes on the coast of the USA. Historical data on hurricanes and tropical storms are identified and curated to support supervised learning. A novel storm damage ratio is introduced to address the inherent challenge of comparing damage to regions with distinct assets and population. Multiple mathematical models to predict economic impacts from tropical events are created using machine learning methods, and the results are compared. Finally, the storm features that most influence the accuracy of predictions are identified and ranked. © 2021, The Author(s), under exclusive licence to Springer Nature B.V.
关键词	Economic impacts Machine learning Storm damage Tropical cyclones
语种	英语
来源期刊	Natural Hazards
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/206659
作者单位	School of Industrial and Systems Engineering, University of Oklahoma, Norman, OK 73071, United States
推荐引用方式 GB/T 7714	Wendler-Bosco V.,Nicholson C.. Modeling the economic impact of incoming tropical cyclones using machine learning[J],2021.
APA	Wendler-Bosco V.,&Nicholson C..(2021).Modeling the economic impact of incoming tropical cyclones using machine learning.Natural Hazards.
MLA	Wendler-Bosco V.,et al."Modeling the economic impact of incoming tropical cyclones using machine learning".Natural Hazards (2021).