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基于船位数据的南极磷虾中层拖网船作业状态特征提取

苏冰 何瑞麟 赵国庆 蒋沛雯 李阳 商宸 韩海斌 沈烈 张衡

海洋渔业2025,Vol.47Issue(5):650-661,12.
海洋渔业2025,Vol.47Issue(5):650-661,12.

基于船位数据的南极磷虾中层拖网船作业状态特征提取

Extraction of operational status features of Antarctic krill midwater trawlers based on vessel location data

苏冰 1何瑞麟 2赵国庆 3蒋沛雯 4李阳 5商宸 6韩海斌 6沈烈 7张衡6

作者信息

  • 1. 大连海洋大学航海与船舶工程学院,辽宁大连 116023||青岛海洋科技中心崂山实验室,山东青岛 266237||中国水产科学研究院东海水产研究所,农业农村部远洋与极地渔业创新重点实验室,上海 200090||河南科技职业大学,河南周口 461300
  • 2. 大连海洋大学航海与船舶工程学院,辽宁大连 116023||中国水产科学研究院东海水产研究所,农业农村部远洋与极地渔业创新重点实验室,上海 200090||农业农村部渔业遥感重点实验室,上海 200090
  • 3. 中国水产科学研究院东海水产研究所,农业农村部远洋与极地渔业创新重点实验室,上海 200090
  • 4. 中国水产科学研究院东海水产研究所,农业农村部远洋与极地渔业创新重点实验室,上海 200090||安徽师范大学,安徽芜湖 241000
  • 5. 大连海洋大学航海与船舶工程学院,辽宁大连 116023||青岛海洋科技中心崂山实验室,山东青岛 266237||中国水产科学研究院东海水产研究所,农业农村部远洋与极地渔业创新重点实验室,上海 200090
  • 6. 青岛海洋科技中心崂山实验室,山东青岛 266237||中国水产科学研究院东海水产研究所,农业农村部远洋与极地渔业创新重点实验室,上海 200090||农业农村部渔业遥感重点实验室,上海 200090||上海海洋大学,上海 201306
  • 7. 大连海洋大学航海与船舶工程学院,辽宁大连 116023
  • 折叠

摘要

Abstract

The operation characteristics of Antarctic krill midwater trawlers based on the location data were investigated.The VMS location data were collected from three Chinese Antarctic krill vessels:Furonghai,Longteng,and Longfa.The operational statuses were classified as fishing,sailing and drifting,and they were evaluated preliminarily according to a method combining the threshold of speed and heading data.The evaluation results were compared with fishing logbooks for verification,and finally,the actual status of the vessels was determined as a dataset.The dataset was divided into training set and test set by 8∶2.A deep neural networks(DNN)multiple operational status identification algorithm was constructed based on speed,heading,duration,latitude and longitude.The operation days,operation date and corresponding operation location information of the fishing vessels were extracted,compared and verified with the actual recorded fishing log data.The results show that:the errors between the extracted result and the actual recorded result are small,and the monthly difference in the number of operation days is within 0-2 d,the average accuracy rate is 93.88%;the difference in operation distance is small,and 94%of the total is within 20 km;compared with k-nearest neighbor(KNN),logistic regression,Bayesian algorithm and decision tree,DNN performed better in vessel operational status identification,with the best accuracy of 87.04%.The research can provide some references for identifying the operational status,fishing and fisheries management of Antarctic krill trawlers.

关键词

南极磷虾/船位数据/作业状态/深度学习

Key words

Antarctic krill/vessel location data/operational status/deep learning

分类

农业科技

引用本文复制引用

苏冰,何瑞麟,赵国庆,蒋沛雯,李阳,商宸,韩海斌,沈烈,张衡..基于船位数据的南极磷虾中层拖网船作业状态特征提取[J].海洋渔业,2025,47(5):650-661,12.

基金项目

青岛海洋科技中心山东省专项经费(2022QNLM030002-1) (2022QNLM030002-1)

国家重点研发计划(2022YFC2807504) (2022YFC2807504)

中国水产科学研究院东海水产研究所中央级公益性科研院所基本科研业务费专项资金(2021M06) (2021M06)

海洋渔业

OA北大核心

1004-2490

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