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The Rise of Machine Learning in Hydrology

机译:The Rise of Machine Learning in Hydrology

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摘要

SINCE 2015, ALPHAGO AND ITS SUCCESSOR PROGRAMShave defeated human Go professionals using artificialintelligence. AlphaGo was developed to test how wella neural network using deep learning can compete atthe game Go and other board games, such as chess,without being taught the rules. The tremendous growthin AI, machine learning (ML), and big data has openeda new era, sometimes called the Fourth IndustrialRevolution. From the targeting of more effectivebusiness advertisements to the greater accuracy of livecaptions on the media, ML has fundamentally changedthe way we live and work. Now data scientists, computerscientists, and hydrologists are coming together touse ML to advance our understanding of hydrologicalsystems.

著录项

  • 来源
    《Water resources impact》 |2022年第6期|22-23|共2页
  • 作者

    Xiang Li; John L. Nieber;

  • 作者单位

    University of Minnesota;

    Department of Bioproducts and Biosystems Engineering at the University of Minnesota,Soil Physics and Hydrology division in the Soil Science Society of America;

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  • 正文语种 英语
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