Submersible Position Prediction and Identification Based on Hybrid Neural Network Algorithm and Monte Carlo Method-Reference-Cited by-同舟云学术

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Submersible Position Prediction and Identification Based on Hybrid Neural Network Algorithm and Monte Carlo Method

Published:2024-06-12 Issue: Volume: Page:610-615
ISSN:
Container-title:2024 2nd International Conference on Mechatronics, IoT and Industrial Informatics (ICMIII)
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Author:

Xie Lingyi¹,Li Xinqi²,Zhang Mufan³

Affiliation:

1. Southern University of Science and Technology,Department of Mechanical and Energy Engineering,Shenzhen,China

2. Southern University of Science and Technology,Department of Information Systems and Management Engineering,Shenzhen,China

3. Southern University of Science and Technology,Department of Statistics and Data Science,Shenzhen,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10659854/10659821/10660083.pdf?arnumber=10660083

Reference5 articles.

1. A time–frequency physics-informed model for real-time motion prediction of semi-submersibles

2. Short-term prediction of hydrodynamic response of a novel semi-submersible FOWT platform under wind, current and wave loads

3. Wave runup prediction for a semi-submersible based on temporal convolutional neural network

4. Short-term motion prediction of a semi-submersible by combining LSTM neural network and different signal decomposition methods

5. Investigation on dynamic performance of semi-submersible aquaculture platform in two mooring forms

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