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학술지 Evaluation of Disaster Response System Using Agent-Based Model With Geospatial and Medical Details
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배장원, 신교홍, 이현록, 이현진, 이태식, 김주현, 차원철, 김기운, 문일철
IEEE Transactions on Systems, Man and Cybernetics : Systems, v.48 no.9, pp.1454-1469
18HS3200, 점진적 기계학습 기반 자가진화(Self-Evolving) 에이전트 시뮬레이션을 이용한 사회변화 예측분석 기술 개발, 백의현
Many disasters have occurred around the world and have caused sizable damage. A disaster, called a mass casualty incident (MCI), generates a large number of casualties that overwhelm the capacity of local medical resources, and the disaster responses to the MCI requires many interactions among the disaster responders. To evaluate the efficiency of the disaster responses against MCIs, this paper proposes an agent-based model describing the cooperations among the responders during the overall process in the disaster responses from transporting patients to their definitive care. In particular, the proposed model includes geospatial details, such as the road network and the location of hospitals around the disaster scene, and medical information, such as the distribution of medical resources and transporting units, in the region of interest to discover the key factors of the disaster response system that customized to the target region. The case study in this paper presents that the proposed approach was applied to describe a disaster response system and illustrates how the additional details are utilized to analyze the disaster response system. We expect that the proposed method can provide comprehensive insights to a disaster response system of interest, and it can be used as groundwork for improving the disaster response system.
KSP 제안 키워드
Case studies, Disaster Response, Key factor, Mass casualty incident, Number of casualties, Proposed model, Region Of Interest(ROI), Road networks, agent-based model(ABM), medical information, medical resources