@inproceedings{ce787c80400d4635b84384b32527aba6,
title = "An accurate cavitation prediction thruster model based on Gaussian process regression",
abstract = "Cavitation effect generates when the propeller of the thruster revolves close to the free surface which can lead to thrust attenuation and high noise. In this paper, a Gaussian process regression based thruster model which considers cavitation effect is presented. The conventional thruster model is introduced at first. Afterwards, the error of the conventional thruster model caused by cavitation effect is analyzed and the cavitation prediction thruster model based on Gaussian process regression is proposed. The effectiveness of the proposed model is validated via proof-of-concept experiments. The experimental results demonstrate the accuracy of the proposed model with the error less than the conventional model.",
keywords = "Gaussian process, cavitation, thruster model, underwater vehicle",
author = "Yang Luo and Jianguo Tao and Zhandong Li and Liang Ding and Zongquan Deng and Hao Sun and Xingguo Song",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 2017 IEEE International Conference on Robotics and Biomimetics, ROBIO 2017 ; Conference date: 05-12-2017 Through 08-12-2017",
year = "2017",
month = jul,
day = "2",
doi = "10.1109/ROBIO.2017.8324478",
language = "英语",
series = "2017 IEEE International Conference on Robotics and Biomimetics, ROBIO 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1--6",
booktitle = "2017 IEEE International Conference on Robotics and Biomimetics, ROBIO 2017",
address = "美国",
}