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A Method for Formulizing Disaster Evacuation Demand Curves Based on SI Model

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      Abstract

      The prediction of evacuation demand curves is a crucial step in the disaster evacuation plan making, which directly affects the performance of the disaster evacuation. In this paper, we discuss the factors influencing individual evacuation decision making (whether and when to leave) and summarize them into four kinds: individual characteristics, social influence, geographic location, and warning degree. In the view of social contagion of decision making, a method based on Susceptible-Infective (SI) model is proposed to formulize the disaster evacuation demand curves to address both social influence and other factors’ effects. The disaster event of the “Tianjin Explosions” is used as a case study to illustrate the modeling results influenced by the four factors and perform the sensitivity analyses of the key parameters of the model. Some interesting phenomena are found and discussed, which is meaningful for authorities to make specific evacuation plans. For example, due to the lower social influence in isolated communities, extra actions might be taken to accelerate evacuation process in those communities.

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      The structure and function of complex networks

       M. Newman (2003)
      Inspired by empirical studies of networked systems such as the Internet, social networks, and biological networks, researchers have in recent years developed a variety of techniques and models to help us understand or predict the behavior of these systems. Here we review developments in this field, including such concepts as the small-world effect, degree distributions, clustering, network correlations, random graph models, models of network growth and preferential attachment, and dynamical processes taking place on networks.
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        • Record: found
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        Complex networks: Structure and dynamics

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          • Record: found
          • Abstract: not found
          • Article: not found

          A Theory of Fads, Fashion, Custom, and Cultural Change as Informational Cascades

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            Author and article information

            Affiliations
            MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology, School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China; 14120879@ 123456bjtu.edu.cn
            Author notes
            [* ]Correspondence: xdyan@ 123456bjtu.edu.cn ; Tel.: +86-184-0160-6819
            Contributors
            Role: Academic Editor
            Journal
            Int J Environ Res Public Health
            Int J Environ Res Public Health
            ijerph
            International Journal of Environmental Research and Public Health
            MDPI
            1661-7827
            1660-4601
            10 October 2016
            October 2016
            : 13
            : 10
            27735875 5086725 10.3390/ijerph13100986 ijerph-13-00986
            © 2016 by the authors; licensee MDPI, Basel, Switzerland.

            This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license ( http://creativecommons.org/licenses/by/4.0/).

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