수산해양기술연구 (Journal of the Korean Society of Fisheries and Ocean Technology)

  • 제58권4호
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  • Pages.299-309
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  • 2022
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  • 2671-9940(pISSN)
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  • 2671-9924(eISSN)
한국수산해양기술학회 (The Korean Society of Fisheries and Ocean Technology)
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외력에 의한 채낚기 어선의 표류 추정

Estimation of leeway of jigging fishing vessels by external factors

  • 이창헌 (제주대학교 해양과학대학) ;
  • 김광일 (제주대학교 해양과학대학) ;
  • 김주성 (목포해양대학교 항해학부) ;
  • 유상록 ((주)미래해양정보기술 기업부설연구소)
  • Chang-Heon, LEE (College of Ocean Sciences, Jeju National University) ;
  • Kwang-Il, KIM (College of Ocean Sciences, Jeju National University) ;
  • Joo-Sung, KIM (Division of Navigation Science, Mokpo National Maritime University) ;
  • Sang-Lok, YOO (Research Institute, Future Ocean Information Technology, Inc.)
  • 투고 : 2022.10.12
  • 심사 : 2022.11.18
  • 발행 : 2022.11.30
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초록

Among the fishing vessels operating in the coastal waters, jigging fishing vessels were considered representative vessels engaged only by wind, sea, tide, and external force. Then, a fishing vessel with a length of shorter than 10 m from July 1, 2018 to August 5, 2019 was studied to obtain a drift prediction model by multiple regression analysis. In the correlation analysis between variables for leeway of speed and direction, the speed and direction of tidal seem to be the most affected in coastal waters. Therefore, it should be considered an explanatory variable when conducting drift tests. As a result of multiple regression analysis on the predicted equations of leeway speed and direction due to the external force on the drift of the fishing vessel, p < 0.000 was considered significant in the F-test, but the coefficient of determination was 55.2% and 37.8%. The effect on the predicted leeway speed was in the order of the tidal speed and current speed. In addition, the impact on the predicted leeway direction was in the order of the tidal speed and current speed. ŷ(m/s) = - 0.0011(x1) + 0.9206(x2) + 0.0001(x3) + 0.0002(x4) + 0.0050(x5) + 0.0529(x6) + 0.2457 ŷ(degree) = 0.6672(x1) + 93.1699(x2) + 0.0585(x3) - 0.0244(x4) - 1.2217(x5) + 4.6378(x6) - 0.0837

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과제정보

이 논문은 2022년 정부(과학기술정보통신부)의 재원으로 과학기술일자리진흥원의 지원(지역산업연계 대학 Open-Lab 육성지원사업, No. 1711173699) 및 2022년도 정부(해양수산부) 재원으로 해양수산과학기술진흥원의 지원(AI 기반 스마트 어업관리 시스템 개발사업, No. 1525012509)과 2022년도 정부(교육부) 재원으로 한국연구재단의 지원을 받아 수행된 연구임(3단계산학연협력선도대학육성사업(LINC3.0), No. 1345356152).

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