Applying artificial intelligence to predict the fishing performance of stow net constructed with noctilucent sticks
文献类型： 外文期刊
作者： Liu, Wei 1 ; Min, Minghua 1 ; Wang, Zhongqiu 1 ; Wang, Lei 1 ; Liu, Yongli 1 ; Qi, Guangrui 1 ; Zhang, Xun 1 ; Wang, Lumin 1 ;
作者机构： 1.Chinese Acad Fishery Sci, East China Sea Fisheries Res Inst, Key Lab Ocean & Polar Fisheries, Minist Agr & Rural Affairs, Shanghai 200090, Peoples R China
2.Qingdao Marine Sci & Technol Ctr, Qingdao 266237, Peoples R China
关键词： Stow net; Noctilucent stick; Catch efficiency; Lunar phase and tidal cycle; Artificial intelligence prediction
期刊名称：REGIONAL STUDIES IN MARINE SCIENCE （ 影响因子：2.4； 五年影响因子：2.4 ）
ISSN： 2352-4855
年卷期： 2025 年 89 卷
页码：
收录情况： SCI
摘要： The application of artificial light to attract marine organisms was demonstrated to enhance fishing gear efficiency. This study presented a novel stow net design incorporating noctilucent sticks to optimize catch performance. Specifically, the research examined the impact of different colores of noctilucent sticks on the efficiency of catch in stow nets. The results revealed the use of noctilucent sticks could significantly increase the catch weight of stow nets (p < 0.01). Notably, the color of the noctilucent sticks influenced their effectiveness, with olive green sticks increasing catch weight by 40.65 %, followed by azure sticks (12.57 %) and bluish green sticks (8.88 %). The predominant species caught was the small yellow croaker, whose catch proportion rose from 19.18 % to 22.80 % due to the noctilucent sticks. In addition, a comprehensive analysis was conducted using the generalized additive model (GAM) to assess the impact of noctilucent sticks, lunar phases, and tidal cycles on stow net catch weights, complemented by a backpropagation (BP) neural network for predictive modeling of catch weights. It was confirmed that lunar phase, tidal cycle, and noctilucent stick presence significantly affected stow net catches. While the BP neural network predictions closely matched the measured data, with the accuracy exceeding 89.63 % and 91.72 %. This study provided theoretical guidance for stow net fishing practices in the Yellow Sea.
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