인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록·키워드
Based on the inadequacies and neglect of the equity of refuge resources, refuge demands and the evacuation allocation of traditional methodologies, this study put forwards the multi-objectives layout optimization model of shelters which firstly realizes the maximum equity of shelter location. Our approach has the objectives of maximizing equity, minimizing overall egress time and minimizing the quantity of new shelters. The high-precision population is established through mobile signaling data, while the optimization model adopts a circular circulatory allocation rule derived from a gravity model. The shorter the evacuation time, the larger the shelter capacity and thus more refugees are allocated to the shelter. The evacuation time is determined by the application programming interface (API) of the Baidu Map open platform with Python, which exhibits the authentic evacuation paths and real-time traffic conditions. This study designs a three-stage algorithm ‘genetic algorithm-exhaustive method-evaluation’. The first process of algorithm calculates the minimum quantity of new shelters; the second process selects the feasible layout schemes and determines Pareto optimum solutions; and the third stage evaluates the Pareto optimum solution based on the shelter construction cost and the accessibility from shelters to emergency supply storage points to determine the best location scheme. This study regards Xin Jiekou district in Nanjing as a case area to demonstrate reliability and availability of the proposed methodology.
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
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