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Forecasting tropical cyclones wave height using bidirectional gated recurrent unit

机译:使用双向门控复发单位预测热带旋风波高

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摘要

A bidirectional Gated recurrent units (BiGRU) network is proposed for the prediction of wave height during tropical cyclones (TC). We used a data set of 28 TC events collected from 14 buoys in different environments over the past 9 years. We use buoy data and TC data collected from 27 TC events for training and use six different parameters to predict the wave height in different lead time, the trained model was used to predict the wave heights of 10 buoys during a new typhoon, compared to machine learning models, the results illustrate that BiGRU's predictive performance is stable, especially for prediction 24 hours in advance, and the model can still be effectively used for real-time wave height prediction when the performance of traditional machine learning methods is severely degraded. In terms of long-term prediction, the model's performance exceeds that of existing methods.
机译:提出了一种双向门控复发单元(BigRU)网络,用于在热带气旋(TC)期间的波高。 我们在过去9年中使用了28个TC事件的数据集,从14个浮标中收集的14个浮标。 我们使用从27个TC事件中收集的浮标数据和TC数据进行培训,并使用六种不同的参数来预测不同的换通时间的波高,训练模型用于预测与机器相比的新台风期间10浮标的波浪高度。 学习模型,结果说明了Bigru预测性能稳定,特别是预测预先预测24小时,并且当传统机器学习方法的性能严重降低时,该模型仍然可以有效地用于实时波高度预测。 在长期预测方面,模型的性能超过现有方法。

著录项

  • 来源
    《Ocean Engineering》 |2021年第15期|108795.1-108795.11|共11页
  • 作者单位

    China Univ Petr Sch Geosci Qingdao 266580 Shandong Peoples R China;

    China Univ Petr Coll Comp Sci & Technol Qingdao 266580 Shandong Peoples R China|Univ Politecn Madrid Fac Comp Sci Dept Artificial Intelligence Campus Montegancedo Madrid 28660 Spain;

    Southern Marine Sci & Engn Guangdong Lab Zhuhai Zhuhai 519082 Peoples R China;

    China Univ Petr Coll Comp Sci & Technol Qingdao 266580 Shandong Peoples R China;

    China Univ Petr Coll Comp Sci & Technol Qingdao 266580 Shandong Peoples R China;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Deep learning; Wave height prediction; Tropical cyclones; BiGRU;

    机译:深度学习;波浪高预测;热带气旋;Bigru;

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