Titlebook: Intelligent Systems for Crisis Management; Geo-information for Sisi Zlatanova,Rob Peters,Hans Scholten Book 2013 Springer-Verlag Berlin He

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Multi-agent Evacuation Simulation Data Model with Social Considerations for Disaster Management Contvacuation simulation that includes the relevant social parameters identified in the emergency literature. The model is composed of three sub-models that describe the agents, their context and behaviour, the dynamic environment in which the agents evolve and the parameters of the evacuation scenario.

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An A*-Based Search Approach for Navigation Among Moving ObstaclesWe propose a model to represent the dynamic network and an adapted A* algorithm for shortest path computations in the context of moving obstacles. Moreover, this paper presents a web-based application for route planning. It integrates an agent-based simulation tool for both analysis of the dynamic r

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Interactive Simulation and Visualisation of Realistic Flooding Scenariosre sophisticated algorithms that promote this goal. Related work in the field is done on small-scale examples and abstract computational models. We work on large-scale, high-resolution, realistic computations while maintaining interactivity. For this we use aerial terrain LiDAR point clouds of The N

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Granular Computing and Dempster–Shafer Integration in Seismic Vulnerability Assessmenton making a complicated disaster management problem. To overcome this problem, this paper proposes an integrated model based upon the granular computing and Dempster–Shafer to extract classification rules for classification of urban areas regarding seismic vulnerability. One of the significant prope

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Managing Satellite Precipitation Data (PERSIANN) Through Web GeoServices: A Case Study in North Vietal Neural Network (PERSIANN) and rain gauges (RG) to investigate the interpolation of RG data. Furthermore, we also estimate a correlation and examined a percentage of simultaneous rain or no-rain between them. We realize that correlation between PERSIANN and gauge data meets expectation value when

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