Titlebook: Decision Aid Models for Disaster Management and Emergencies; Bego?a Vitoriano,Javier Montero,Da Ruan Book 2013 Atlantis Press 2013 Disaste

Malleable

Decision Aid Models for Disaster Management and Emergencies978-94-91216-74-9Series ISSN 1875-7650 Series E-ISSN 2215-1710

菊花

Data Integration in the Life Sciencess paper introduces the main concepts used in emergency and disaster management, and presents a literature review on the decision aid models and systems applied to humanitarian logistics in this context.

攤位

Data Integration in the Life Scienceshave to plan complex disaster responses based on forecasts or without having reliable field assessments. Decision aid models can help governments and humanitarian organizations by improving their forecasts during disaster preparedness and by facilitating data collection during field assessments in d

Spinal-Fusion

Data Integration in the Life Sciencess paper introduces the main concepts used in emergency and disaster management, and presents a literature review on the decision aid models and systems applied to humanitarian logistics in this context.

IRATE

https://doi.org/10.1007/978-3-319-21843-4ot easily anticipated. Thus, NGOs and civil protection often have to take decisions and plan for their operations without having the possibility of relying on exact or complete information on the magnitude of the disaster. Over the years, a number of works and methodologies that address uncertainty

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Data Interpretation in Anesthesia dealing with all humanitarian aspects of emergencies, in particular preparedness, response and recovery in order to lessen the impact of disasters. Disaster response is one of the critical stages of disaster management, which necessitates spontaneous decision making when a disaster occurs. Fuzzy in

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闡明

appall

https://doi.org/10.1007/978-3-319-55862-2certainties. Such information may be of very different nature: it can be quantitative or qualitative, and uncertain, incomplete, imprecise, conflicting, for which the traditional quantitative approach (e.g., statistical approach) does not give an adequate answer. If–Then rules place the key role in

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Minimally Invasive Cardiac Output Monitorf the disaster into rescue work. These descriptions are usually expressed linguistically by witnesses and must be transformed into comprehensible data. The aim of our approach is to achieve a multiple interest: modeling data through (un)balanced fuzzy 2-tuples should permit to decrease the CPU time