A systematic review of prediction methods for emergency management

Di Huang, Shuaian Wang, Zhiyuan Liu

Research output: Journal article publicationReview articleAcademic researchpeer-review

8 Citations (Scopus)

Abstract

With the trend of global warming and destructive human activities, the frequent occurrences of catastrophes have posed devastating threats to human life and social stability worldwide. The emergency management (EM) system plays a significant role in saving people's lives and reducing property damage. The prediction system for the occurrence of emergency events and resulting impacts is widely recognized as the first stage of the EM system, the accuracy of which has a significant impact on the efficiency of resource allocation, dispatching, and evacuation. In fact, the number and variety of contributions to prediction techniques, such as statistic analysis, artificial intelligence, and simulation method, are exploded in recent years, motivating the need for a systematic analysis of the current works on disaster prediction. To this end, this paper presents a systematic review of contributions on prediction methods for emergency occurrence and resource demand of both natural and man-made disasters. Through a detailed discussion on the features of each type of emergency event, this paper presents a comprehensive survey of state-of-the-art prediction technologies which have been widely applied in EM. After that, we summarize the challenges of current efforts and point out future directions.

Original languageEnglish
Article number102412
JournalInternational Journal of Disaster Risk Reduction
Volume62
DOIs
Publication statusPublished - Aug 2021

Keywords

  • Artificial intelligence
  • Disaster
  • Emergency management system
  • Prediction methods
  • Resource demand
  • Review

ASJC Scopus subject areas

  • Geotechnical Engineering and Engineering Geology
  • Safety Research
  • Geology

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