• Corpus ID: 240353773

Probabilistic prediction of the heave motions of a semi-submersible by a deep learning problem model

  title={Probabilistic prediction of the heave motions of a semi-submersible by a deep learning problem model},
  author={Xiaoxian Guo and Xiantao Zhang and Xinliang Tian and Wenyue Lu and Xin Li},
The real-time motion prediction of a floating offshore platform refers to forecasting its motions in the following oneor two-wave cycles, which helps improve the performance of a motion compensation system and provides useful early warning information. In this study, we extend a deep learning (DL) model, which could predict the heave and surge motions of a floating semi-submersible 20 to 50 seconds ahead with good accuracy, to quantify its uncertainty of the predictive time series with the help… 



Predicting heave and surge motions of a semi-submersible with neural networks

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  • Computer Science
    2017 IEEE International Conference on Data Mining Workshops (ICDMW)
  • 2017
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