A Data Fusion System for Simulation of Critical Scenarios and Decision-Making

The decision-making (DM) process in critical environments is a complex process that can be simulated due to current telematic capabilities, which allow the real time interaction of large amounts of data. This document describes the proposed architecture from a research process, developed by the FAC...

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Veröffentlicht in:Ciencia e ingeniería neogranadina 2019-11, Vol.30 (1), p.89-106
Hauptverfasser: Florez Zuluaga, Jimmy Anderson, Patiño Carrasco, Esteban, Ortega Pabon, Jose David, Gallego Leon, Kelly, Quintero Montoya, O. Lucia
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Sprache:eng
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Zusammenfassung:The decision-making (DM) process in critical environments is a complex process that can be simulated due to current telematic capabilities, which allow the real time interaction of large amounts of data. This document describes the proposed architecture from a research process, developed by the FAC Aerospace Technology Development Center (CETAD), where using computational and expert system tools, allowed to create a computational environment for decision maker evaluated his options to prepares for real events, simulating characteristics, resources and strategies in a real time environment. This document describes an investigation product resulted in a simulation system, based on a combination of fuzzy logic, genetic algorithms and decision trees which let modelled and simulated various entities and their automatic response according to simulated patterns and situations, in which, through operators, decision maker can modify entities behaviour, according to parameterized restrictions and physical conditions. Also based on business intelligence tools, reports are generated to evaluate the decisions made. This type of technologies improves planning capacity and facilitate the decision-making process. System allows simulating any media deployment in national security and critical events context. Thus, a case study was developed for implementation of a support in natural disaster scenario simulation
ISSN:0124-8170
1909-7735
DOI:10.18359/rcin.4131