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English(EN) Machine Learning in Fish Farming

机器学习通过先进的人工智能技术革新鱼类养殖业

一篇新发表在arXiv上的章节详细介绍了机器学习(ML)技术在革新鱼类养殖业中的应用。文章探讨了包括随机森林、卷积神经网络、循环神经网络、图神经网络以及大型语言模型在内的各种ML模型如何改进水产养殖运营。该章节重点介绍了生物量估算、物种识别、行为分析和环境预测等关键应用,并强调了ML与物联网的集成,以实现实时监控和决策支持,从而促进更可持续和更具生产力的实践。 AI

影响 通过先进的人工智能应用提高水产养殖业的效率和可持续性。

排序理由 该集群包含一篇发表在arXiv上的研究论文,详细介绍了机器学习技术的应用。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.LG 阅读 →

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机器学习通过先进的人工智能技术革新鱼类养殖业

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该集群包含一篇发表在arXiv上的研究论文,详细介绍了机器学习技术的应用。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.LG TIER_1 English(EN) · Fearghal O'Donncha, Nikos Papandroulakis, Jennie Korus, Abigail Langbridge, Alexander Timms, Konstantinos Topouzelis, Abdul Baseer Khan, Shree Rama Kamal Kumar Vegu, Mahtab Sarvmaili, Ryan Mowat, Rhanna Turberville, Tyler Sclodnick, Christopher Whidden ·

    机器学习在鱼类养殖中的应用

    arXiv:2609.13919v1 Announce Type: new Abstract: This chapter explores how machine learning (ML) is transforming aquaculture, with a particular focus on enhancing decision-making processes and improving operational efficiency. The chapter is structured to first introduce the chall…