Mackerel and Herring on the Move A Migration Research Based on Deep Q-network

Y. Kang, Yilin Chai, Xiaofan Bai, Yuxiao Du, Xinlu Zhang
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引用次数: 1

Abstract

With the development of computer technology, reinforcement learning algorithm is gradually applied in ecology. When the temperature changes greatly, mackerel and herring will not be able to sustain their lives, at which time they will choose to migrate to habitat suitable for their survival and reproduction. This will greatly affect the economic benefits of fishing companies which fishing in the fixed sea area. Therefore, this paper tries to find a reasonable method to predict the migration location of these two species of fish in the foreseeable future. To understand more clearly the survival status of herring and mackerel in the waters near Scotland, we collected a large amount of reliable data and established a prediction model based on Deep Q-Network (DQN). Given that there will be no dangerous situation at sea to affect the fishing operation, the habitats of herring and mackerel will gradually move to high latitudes in the next 50 years.
基于深度q -网络的鲭鱼和鲱鱼迁徙研究
随着计算机技术的发展,强化学习算法逐渐在生态学中得到应用。当温度变化较大时,鲭鱼和鲱鱼将无法维持其生命,此时它们会选择迁移到适合其生存和繁殖的栖息地。这将极大地影响在固定海域捕捞的渔业公司的经济效益。因此,本文试图找到一种合理的方法来预测这两种鱼类在可预见的未来的迁徙位置。为了更清楚地了解苏格兰附近海域鲱鱼和鲭鱼的生存状况,我们收集了大量可靠的数据,建立了基于Deep Q-Network (DQN)的预测模型。考虑到海上不会出现影响捕捞作业的危险情况,鲱鱼和鲭鱼的栖息地将在未来50年内逐渐向高纬度地区迁移。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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