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Special Issue "Sustainable Emergency Management based on Intelligent Information Processing"

A special issue of Sustainability (ISSN 2071-1050).

Deadline for manuscript submissions: 31 December 2019

Special Issue Editors

Guest Editor
Prof. Dr. Xiao-Guang Yue

Rattanakosin International College of Creative Entrepreneurship, Rajamangala University of Technology Rattanakosin, Thailand; International Engineering and Technology Institute, Hong Kong and USA
Website | E-Mail
Interests: sustainable risk management; intelligent information processing
Guest Editor
Prof. Dr. Marc A. Rosen

Faculty of Engineering and Applied Science, University of Ontario Institute of Technology, Canada
Website | E-Mail
Interests: sustainability; sustainable development; energy; efficiency; environmental impact; economics; ecology; sustainable engineering and design

Special Issue Information

Dear Colleagues,

Sustainable emergency management plays a key role in social development and technological applications. Sustainable emergency management involves many aspects of management, engineering, and technology, and we may need to discuss the following topics: sustainable recognition or identification of risks; sustainable ranking or evaluation of risks; sustainable response to significant risks; sustainable tolerance of emergency management; sustainable treatment of emergency management; sustainable transfer of emergency management; sustainable termination of emergency management; sustainable resource controls and planning; sustainable reaction planning; sustainable reporting and monitoring risk performance; sustainable review of the risk management framework; sustainable emergency management and education. Sustainable emergency management is very complicated, involves many factors and data, and also needs to face calculation, modeling, and simulation methods and problems.

At the same time, we have entered the era of big data and artificial intelligence. It is a faster way to use information technology to research and deal with sustainable issues. Intelligent information processing (IIP) is one of the most important components of big data and artificial intelligence. Intelligent information processing methods can be useful tools for analyzing, managing, and controlling risks. The main topics of IIP include multi-agent systems, automatic reasoning, big data mining, cloud computing, cognitive modeling, computational intelligence, deep learning, evolutionary computation, image processing, information retrieval, knowledge-based systems, knowledge engineering, machine learning, natural language processing, neural computing, and web intelligence. In short, IIP is a powerful tool.

Sustainable emergency management based on IIP theory, systems, modeling, and simulation is very important for current and future research. We encourage researchers, teachers, students, engineers, academicians, as well as industrial professionals from all over the world to present their current insights in this Special Issue entitled “Sustainable Emergency Management Based on Intelligent Information Processing”.

All the best,

Prof. Dr. Xiao-Guang Yue
Prof. Dr. Marc A. Rosen
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • sustainable recognition or identification of risks
  • sustainable ranking or evaluation of risks
  • sustainable response to significant risks
  • sustainable tolerance of emergency management
  • sustainable treatment of emergency management
  • sustainable transfer of emergency management
  • sustainable termination of emergency management
  • sustainable resource controls and planning
  • sustainable reaction planning
  • sustainable reporting and monitoring risk performance
  • sustainable review of the risk management framework
  • sustainable emergency management and education

Published Papers (1 paper)

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Research

Open AccessArticle A Decision-Making Algorithm for Maritime Search and Rescue Plan
Sustainability 2019, 11(7), 2084; https://doi.org/10.3390/su11072084
Received: 1 March 2019 / Revised: 28 March 2019 / Accepted: 4 April 2019 / Published: 8 April 2019
PDF Full-text (3499 KB) | HTML Full-text | XML Full-text
Abstract
With the development of the maritime economy, sea traffic is becoming more and more crowded, and sea accidents are also increasing. Research on maritime search and rescue decision-making technology cannot be delayed. This paper studies the maritime search and rescue decision algorithm, based [...] Read more.
With the development of the maritime economy, sea traffic is becoming more and more crowded, and sea accidents are also increasing. Research on maritime search and rescue decision-making technology cannot be delayed. This paper studies the maritime search and rescue decision algorithm, based on the optimal search theory. It also analyzes three important concepts: Probability of containment (POC), probability of detection (POD), and probability of success (POS) involved in the maritime search and rescue decision-making process. In this paper, the calculation methods of POC and POD variables have been improved, and the search success rate has been improved to some extent. Finally, an example analysis of the maritime search and rescue incident is given. Through verification, the algorithm proposed in this paper can support maritime search and rescue decisions. Full article
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