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

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

Deadline for manuscript submissions: closed (31 December 2019).

Special Issue Editors

Prof. Dr. Xiao-Guang Yue
Website
Guest Editor
CIICESI, ESTG, Politécnico do Porto, Felgueiras 4610-156, Portugal;
European University Cyprus, Nicosia 1516, Cyprus
Interests: sustainable risk management; intelligent information processing
Special Issues and Collections in MDPI journals

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 1800 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 (4 papers)

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Editorial

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Open AccessEditorial
Sustainable Emergency Management Based on Intelligent Information Processing
Sustainability 2020, 12(3), 1081; https://doi.org/10.3390/su12031081 - 03 Feb 2020
Cited by 3
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 [...] Read more.
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. Full article

Research

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Open AccessArticle
Risk Factor Identification of Sustainable Guarantee Network Based on Logistic Regression Algorithm
Sustainability 2019, 11(13), 3525; https://doi.org/10.3390/su11133525 - 27 Jun 2019
Cited by 5
Abstract
In order to investigate the factors influencing the sustainable guarantee network and its differences in different spatial and temporal scales, logistic regression algorithm is used to analyze the data of listed companies in 31 provinces, municipalities and autonomous regions in China from 2008 [...] Read more.
In order to investigate the factors influencing the sustainable guarantee network and its differences in different spatial and temporal scales, logistic regression algorithm is used to analyze the data of listed companies in 31 provinces, municipalities and autonomous regions in China from 2008 to 2017 (excluding Hong Kong, Macau and Taiwan). The study finds that, overall, companies with better profitability, poor solvency, poor operational capability and higher levels of economic development are more likely to join the guarantee network. On the temporal scale, solvency and regional economic development exert increasing higher impact on the companies’ accession to the guarantee network, and operational capacity has increasingly smaller impact. On the spatial scale, the less close link between company executives and companies in the western region suggests higher possibility to join the guarantee network. The predictive accuracy test results of the logistic regression algorithm show that the training model of the western sample enterprises has the highest prediction accuracy when predicting enterprise behavior of joining the guarantee network, while the accuracy is the lowest in the central region. When forecasting enterprises’ failure to join the guarantee network, the training model of the central sample enterprise has the highest accuracy, while the accuracy is the lowest in the eastern region. This paper discusses the internal and external factors influencing the guarantee network risk from the perspective of spatial and temporal differences of the guarantee network, and discriminates the prediction accuracy of the training model, which means certain guiding significance for listed company management, bank and government to identify and control the guarantee network risk. Full article
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Open AccessArticle
Ranking of Risks for Existing and New Building Works
Sustainability 2019, 11(10), 2863; https://doi.org/10.3390/su11102863 - 20 May 2019
Cited by 5
Abstract
Site safety is one critical factor affecting the sustainability of skyscrapers and decoration, repair, and maintenance projects. Many newly-built skyscrapers exceed 50 storeys in Hong Kong and decoration, repair, and maintenance projects are widely performed to extend the lifespans of buildings. Although many [...] Read more.
Site safety is one critical factor affecting the sustainability of skyscrapers and decoration, repair, and maintenance projects. Many newly-built skyscrapers exceed 50 storeys in Hong Kong and decoration, repair, and maintenance projects are widely performed to extend the lifespans of buildings. Although many cities do not contain skyscrapers at present, this will change in the future. Likewise, more decoration, repair, and maintenance projects will emerge. Thus, the present research, which compares the safety risks among the new and DSR projects, provides insights for builders, policymakers, and safety personnel. Moreover, research studies which rank and compare decoration, repair, and maintenance projects and new skyscraper constructions are scarce. The use of the evidence-based practice approach, which aims to narrow the gap between practice and academia in construction safety research, is the first of its kind. In this paper, we firstly provide a systematic literature review from 1999 to 2019 regarding construction safety, and then study the industry’s perspectives by analysing the construction practitioners’ interview results, court cases, and analytic hierarchy process survey results to compare them with the literature. It is found that the generation gap and prolonged working hours lead to accidents—a phenomenon which is unique in Hong Kong and absent from the literature. It also reveals that most accidents happen on new building sites due to tower crane failure, while those on DSR projects are linked with the circular saw. Although many of the contractors involved in new buildings are wealthier than DSR contractors, it is surprising to learn that lack of funding for safety is the most important factor linked to safety risks on the sites. Full article
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Open AccessArticle
A Decision-Making Algorithm for Maritime Search and Rescue Plan
Sustainability 2019, 11(7), 2084; https://doi.org/10.3390/su11072084 - 08 Apr 2019
Cited by 5
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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