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Sustainable Emergency Management Based on Intelligent Information Processing

descriptionPublicationkeyboard_double_arrow_right Article , Journal 03 Feb 2020Publisher:MDPI AGJournal:Sustainability, volume 12, page 1,081 (eissn: 2071-1050,

Authors: Yu-Meng Luo; Wei Liu; Xiao-Guang Yue; Marc A. Rosen;

doi: 10.3390/su12031081

Sustainable Emergency Management Based on Intelligent Information Processing

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Abstract

In this paper, we introduce how to identify, rank, evaluate, and respond to risks based on intelligent information processing, providing new ideas and research directions for sustainable emergency management. First, we discuss the contributions and deficiencies of the existing research that have informed the development and launch of this Special Issue and, second, we provide an overview of the three articles included. In addition, this article introduces this particular Special Issue, not only to complement the somewhat lacking body of related literature, but also to help contemporary companies deal with issues related to sustainable emergency management based on intelligent information processing.

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Qingdao Binhai University
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Keywords

Environmental effects of industries and plants, TJ807-830, emergency management, artificial intelligence, sustainability, TD194-195, Renewable energy sources, information, Environmental sciences, GE1-350

Impact byBIP!

	citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	27
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Top 1%
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Top 10%
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Top 10%