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
Building emergency communication in disaster areas is a key problem that emergency response needs to solve. Ad hoc Network (ANET) can quickly establish communication networks when public communication infrastructure is disrupted. At present, ground emergency communication deployment based on ANET usually relies on the operator’s experience, which struggles to ensure high-quality deployment in complex urban environments. This paper proposes an ANET nodes spatial optimization deployment algorithm based on 3D Spatial Evolutionary Particle Swarm Optimization (3DSEPSO). A wireless communication transmission rate model that depends on surface buildings and trees is constructed using ground truth communication data. The algorithm incorporates a fitness evaluation model, particle chromosome structure, and an evolutionary mechanism to intelligently deploy ANET nodes. By considering the spatial distribution of buildings and trees, the algorithm can achieve optimal data transmission quality by using a given number of ANET nodes. Experimental results demonstrate that the proposed algorithm significantly outperforms empirical approaches and traditional methods in terms of data transmission rates and quality. Thus, the algorithm provides better support for emergency rescue teams by facilitating more effective and reliable emergency communication.
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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