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渔业研究 ›› 2022, Vol. 44 ›› Issue (4): 407-414.DOI: 10.14012/j.cnki.fjsc.2022.04.012

• 论文与报告 • 上一篇    

机器学习在渔业研究中的应用进展与展望

周文英,史文崇   

  1. 河北科技师范学院数学与信息科技学院,河北 秦皇岛 066004
  • 收稿日期:2022-04-07 修回日期:2022-05-13 出版日期:2022-08-25 发布日期:2022-08-23
  • 通讯作者: 史文崇(1965-),男,副教授,研究生导师,硕士,研究方向:大数据、机器学习、图像处理.E-mail: mr_shi_pb@126.com
  • 作者简介:周文英(1998-),女,硕士研究生,研究方向:农业信息技术、机器学习.E-mail: zhouzz0321@163.com

Application progress and prospect of machine learning applied to fishery research

  • Received:2022-04-07 Revised:2022-05-13 Online:2022-08-25 Published:2022-08-23

摘要: 渔业大数据时代已经到来,一些国家紧跟步伐着手开展渔业大数据研究,而机器学习是大数据研究不可或缺的有效手段。将机器学习技术用于渔业研究,对弥补渔业大数据分析与应用的不足和发展数字、智慧渔业,既非常必要,也非常重要。本文利用文献分析法,研究了国内外将“机器学习”用于渔业研究的现状与发展趋势。根据目前机器学习技术在渔业生产、渔业分类、水质检测、目标识别、渔业服务等领域的研究成果,认为:机器学习已经在渔业研究中发挥重要作用,但机器学习用于微观研究多、宏观研究少;用于静态研究多、动态研究少;用于与其他产业互动研究更为罕见。如今,智能捕捞产品和渔业观测云平台已经出现,物联网技术也为机器学习被广泛地用于渔业研究提供了便利。加强物联网硬件基础设施建设,加强与数据上游的合作与融合,是渔业机器学习应用蓬勃发展的必由之路。机器学习在捕捞作业监管、渔业生态模拟、利用渔业产品生产多种日用品等研究领域,大有可为。

关键词: 机器学习, 渔业研究, 大数据, 数字渔业, 智慧渔业

Abstract: The era of fishery big data has come. Some countries have started to carry out fishery big data research. Machine learning is an indispensable and effective means for big data research. Applying machine learning technology in fishery research is very necessary and important to make up for the deficiency of fishery big data analysis and application, and to develop the digital and intelligent fishery in China. The present situation and developing trend of applying machine learning to fishery research at home and abroad were studied by literature analysis. Based on the current research results of machine learning technology in fishery production, fishery classification, water quality detection, target recognition, fishery services and other fields, it was thought that machine learning had played an important role in fishery research. But machine learning was used for micro research more than macro research. And it was used for static research more than dynamic research. It was used even rarer to study interactively with other industries. At present, intelligent fishing products and some fishery observation cloud platforms had emerged. The technologies of Internet of Things also facilitated the widespread use of machine learning in fishery research. Strengthening the hardware infrastructure construction of Internet of Things, and strengthening the cooperation and integration with upstream data were the only approach for machine learning’s being widely applied in fishery research. Now, machine learning had a promising future in the research fields such as fishing activities’ supervision, fishery ecological simulation and producing a variety of daily necessities with fishery products.

Key words: machine learning, fishery research, big data, digital fishery, intelligent fishery

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