Research on Fishery Trajectory Analysis and Fishing Ground Discrimination Based on CNN

Wenjin Xu, Qingxia Xie, Yue-Wei Ma
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Abstract

With the continuous progress of science and technology, people's production and lifestyle which has lasted for thousands of years are also changing quietly. More and more things, people, data, and the Internet are connected together, which also makes the power of big data calculation and mining increase exponentially. The navigation data of Zhejiang coastal fishermen are recorded by satellite. Using big data calculation can combine the ocean climate information, fishing vessel location information, and the data formed by fishing grounds into a big fishery data platform. After many captains use the data provided by this platform for fishing guidance, they have achieved a very good catch. They use scientific and technological innovation to change fishing methods so that fishermen can no longer rely on heaven for food. The risk is difficult to predict. The research in this paper is to find the common characteristics of fishing grounds by analyzing the navigation data of fishermen in the Zhejiang coastal area recorded by satellite and at the same time, expand the search range to estimate the new fishing ground location. This work can be used to mine data by using convolutional neural network.
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基于CNN的渔业轨迹分析与渔场识别研究
随着科学技术的不断进步,人们延续了几千年的生产和生活方式也在悄然发生着变化。越来越多的物、人、数据、互联网连接在一起,也使得大数据的计算和挖掘能力呈指数级增长。浙江沿海渔民的导航数据是由卫星记录的。利用大数据计算可以将海洋气候信息、渔船位置信息、渔场形成的数据组合成一个渔业大数据平台。许多船长使用该平台提供的数据进行钓鱼指导后,取得了很好的渔获效果。他们用科技创新来改变捕鱼方式,让渔民不再依靠上天来获取食物。这种风险很难预测。本文的研究是通过对浙江沿海地区渔民的卫星导航数据进行分析,找出渔场的共同特征,同时扩大搜索范围,估算新的渔场位置。该工作可用于卷积神经网络的数据挖掘。
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