대한조선학회논문집 (Journal of the Society of Naval Architects of Korea)

  • 제59권6호
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  • Pages.385-392
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  • 2022
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  • 1225-1143(pISSN)
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  • 2287-7355(eISSN)
대한조선학회 (The Society of Naval Architects of Korea)
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Naval Ship Evacuation Path Search Using Deep Learning

  • 박주헌 (충남대학교 선박해양공학과 대학원) ;
  • 유원선 (충남대학교 선박해양공학과) ;
  • 이인석 (충남대학교 선박해양공학과 대학원) ;
  • 최원철 (충남대학교 선박해양공학과)
  • Ju-hun, Park (Grad. School, Dept. of Naval Architecture & Ocean engineering, Chung-nam National University) ;
  • Won-sun, Ruy (Dept. of Naval Architecture and Ocean Engineering, Chung-nam National University) ;
  • In-seok, Lee (Grad. School, Dept. of Naval Architecture & Ocean engineering, Chung-nam National University) ;
  • Won-cheol, Choi (Dept. of Naval Architecture and Ocean Engineering, Chung-nam National University)
  • 투고 : 2022.07.07
  • 심사 : 2022.10.18
  • 발행 : 2022.12.20
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초록

Naval ship could face a variety of threats in isolated seas. In particular, fires and flooding are defined as disasters that are very likely to cause irreparable damage to ships. These disasters have a very high risk of personal injury as well. Therefore, when a disaster occurs, it must be quickly suppressed, but if there are people in the disaster area, the protection of life must be given priority. In order to quickly evacuate the ship crew in case of a disaster, we would like to propose a plan to quickly explore the evacuation route even in urgent situations. Using commercial escape simulation software, we obtain the data for deep neural network learning with simulations according to aisle characteristics and the properties and number of evacuation person. Using the obtained data, the passage prediction model is trained with a deep learning, and the passage time is predicted through the learned model. Construct a numerical map of a naval ship and construct a distance matrix of the vessel using predicted passage time data. The distance matrix configured in one of the path search algorithms, the Dijkstra algorithm, is applied to explore the evacuation path of naval ship.

키워드

과제정보

본 연구는 한국산업기술진흥원(사업명 : 산업혁신인재성장지원사업, 과제번호: P0001968)과 국방기술품질원의 지원(사업명: 글로벌 방위산업 강소기업 육성사업, 과제번호: E200012)하에 수행되었습니다.

참고문헌

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