Ur?ka Demsar, Olga Patenková, & Kirsi Virrantaus. (2007). Centrality measures and vulnerability of spatial networks. In K. Nieuwenhuis P. B. B. Van de Walle (Ed.), Intelligent Human Computer Systems for Crisis Response and Management, ISCRAM 2007 Academic Proceedings Papers (pp. 201–209). Delft: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: Effective management of infrastructural networks in the case of a crisis requires a prior analysis of the vulnerability of spatial networks and identification of critical locations where an interdiction would cause most damage and disruption. This paper presents a preliminary study into how a graph theoretic structural analysis could be used for this purpose. Centrality measures are combined with a dual graph modelling approach in order to identify critical locations in a spatial network. The results of a case study on a street network of a small area in the city of Helsinki indicate that 'betweenness' is the most promising centrality measure for this purpose. Other measures and properties of graphs are under consideration for eventually developing a risk model not only for one but for a group of co-located spatial networks.
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Murray Turoff, Connie White, Linda Plotnick, & Starr Roxanne Hiltz. (2008). Dynamic emergency response management for large scale decision making in extreme events. In B. V. de W. F. Fiedrich (Ed.), Proceedings of ISCRAM 2008 – 5th International Conference on Information Systems for Crisis Response and Management (pp. 462–470). Washington, DC: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: Effective management of a large-scale extreme event requires a system that can quickly adapt to changing needs of the users. There is a critical need for fast decision-making within the time constraints of an ongoing emergency. Extreme events are volatile, change rapidly, and can have unpredictable outcomes. Large, not predetermined groups of experts and decision makers need a system to prepare for a response to a situation never experienced before and to collaborate to respond to the actual event. Extreme events easily require a hundred or more independent agencies and organizations to be involved which usually results in two or more times the number of individuals. To accomplish the above objectives we present a philosophical view of decision support for Emergency Preparedness and Management that has not previously been made explicit in this domain and describe a number of the current research efforts at NJIT that fit into this framework.
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Zhenyu Yu, Chuanfeng Han, & Ma Ma. (2014). Emergency decision making: A dynamic approach. In and P.C. Shih. L. Plotnick M. S. P. S.R. Hiltz (Ed.), ISCRAM 2014 Conference Proceedings – 11th International Conference on Information Systems for Crisis Response and Management (pp. 240–244). University Park, PA: The Pennsylvania State University.
Abstract: The dynamic nature of emergency decision making exerts difficulty to decision makers for achieving effective management. In this regard, we suggest a dynamic decision making model based on Markov decision process. Our model copes with the dynamic decision problems quantitatively and computationally, and has powerful expression ability to model the emergency decision problems. We use a wildfire scenario to demonstrate the implementation of the model, as well as the solution to the firefighting problem. The advantages of our model in emergency management domain are discussed and concluded in the last.
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