Research on Support Vector Regression Model Based on Different Kernels for Short-term Prediction of Ship Motion

Zhihong Nie; Yue Yuan; DIngjie Xu; Feng Shen

doi:10.1109/ISCID.2019.00021

Research on Support Vector Regression Model Based on Different Kernels for Short-term Prediction of Ship Motion

Zhihong Nie
, Yue Yuan
, DIngjie Xu
, Feng Shen

Harbin Institute of Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

11 Scopus citations

Abstract

Short-term prediction of ship motions is of great significance for improving security and efficiency of the offshore operation. Therefore, many prediction models have been proposed by researchers. In recent years, support vector regression algorithm has been proved to be effective to the prediction of ship motions. In this paper, using six degrees of freedom ships motions date collected from real ships, simulation experiments are carried out to analyze the prediction results of the SVR algorithm based on four commonly used kernel functions, and the validity and practicability of these kernel functions for the prediction of ship motions are compared.

Original language	English
Title of host publication	Proceedings - 2019 12th International Symposium on Computational Intelligence and Design, ISCID 2019
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	61-64
Number of pages	4
ISBN (Electronic)	9781728146522
DOIs	https://doi.org/10.1109/ISCID.2019.00021
State	Published - Dec 2019
Externally published	Yes
Event	12th International Symposium on Computational Intelligence and Design, ISCID 2019 - Hangzhou, China Duration: 14 Dec 2019 → 15 Dec 2019

Publication series

Name	Proceedings - 2019 12th International Symposium on Computational Intelligence and Design, ISCID 2019
Volume	1

Conference

Conference	12th International Symposium on Computational Intelligence and Design, ISCID 2019
Country/Territory	China
City	Hangzhou
Period	14/12/19 → 15/12/19

Keywords

kernel function
ship motion
short-term prediction
support vector regression

Access to Document

10.1109/ISCID.2019.00021

Cite this

Nie, Z., Yuan, Y., Xu, DI., & Shen, F. (2019). Research on Support Vector Regression Model Based on Different Kernels for Short-term Prediction of Ship Motion. In Proceedings - 2019 12th International Symposium on Computational Intelligence and Design, ISCID 2019 (pp. 61-64). Article 9098246 (Proceedings - 2019 12th International Symposium on Computational Intelligence and Design, ISCID 2019; Vol. 1). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISCID.2019.00021

Nie, Zhihong ; Yuan, Yue ; Xu, DIngjie et al. / Research on Support Vector Regression Model Based on Different Kernels for Short-term Prediction of Ship Motion. Proceedings - 2019 12th International Symposium on Computational Intelligence and Design, ISCID 2019. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 61-64 (Proceedings - 2019 12th International Symposium on Computational Intelligence and Design, ISCID 2019).

@inproceedings{f98547c6ff5443ad8724a937bfa30ccf,

title = "Research on Support Vector Regression Model Based on Different Kernels for Short-term Prediction of Ship Motion",

abstract = "Short-term prediction of ship motions is of great significance for improving security and efficiency of the offshore operation. Therefore, many prediction models have been proposed by researchers. In recent years, support vector regression algorithm has been proved to be effective to the prediction of ship motions. In this paper, using six degrees of freedom ships motions date collected from real ships, simulation experiments are carried out to analyze the prediction results of the SVR algorithm based on four commonly used kernel functions, and the validity and practicability of these kernel functions for the prediction of ship motions are compared.",

keywords = "kernel function, ship motion, short-term prediction, support vector regression",

author = "Zhihong Nie and Yue Yuan and DIngjie Xu and Feng Shen",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 12th International Symposium on Computational Intelligence and Design, ISCID 2019 ; Conference date: 14-12-2019 Through 15-12-2019",

year = "2019",

month = dec,

doi = "10.1109/ISCID.2019.00021",

language = "英语",

series = "Proceedings - 2019 12th International Symposium on Computational Intelligence and Design, ISCID 2019",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "61--64",

booktitle = "Proceedings - 2019 12th International Symposium on Computational Intelligence and Design, ISCID 2019",

address = "美国",

}

Nie, Z, Yuan, Y, Xu, DI & Shen, F 2019, Research on Support Vector Regression Model Based on Different Kernels for Short-term Prediction of Ship Motion. in Proceedings - 2019 12th International Symposium on Computational Intelligence and Design, ISCID 2019., 9098246, Proceedings - 2019 12th International Symposium on Computational Intelligence and Design, ISCID 2019, vol. 1, Institute of Electrical and Electronics Engineers Inc., pp. 61-64, 12th International Symposium on Computational Intelligence and Design, ISCID 2019, Hangzhou, China, 14/12/19. https://doi.org/10.1109/ISCID.2019.00021

Research on Support Vector Regression Model Based on Different Kernels for Short-term Prediction of Ship Motion. / Nie, Zhihong; Yuan, Yue; Xu, DIngjie et al.
Proceedings - 2019 12th International Symposium on Computational Intelligence and Design, ISCID 2019. Institute of Electrical and Electronics Engineers Inc., 2019. p. 61-64 9098246 (Proceedings - 2019 12th International Symposium on Computational Intelligence and Design, ISCID 2019; Vol. 1).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Research on Support Vector Regression Model Based on Different Kernels for Short-term Prediction of Ship Motion

AU - Nie, Zhihong

AU - Yuan, Yue

AU - Xu, DIngjie

AU - Shen, Feng

PY - 2019/12

Y1 - 2019/12

N2 - Short-term prediction of ship motions is of great significance for improving security and efficiency of the offshore operation. Therefore, many prediction models have been proposed by researchers. In recent years, support vector regression algorithm has been proved to be effective to the prediction of ship motions. In this paper, using six degrees of freedom ships motions date collected from real ships, simulation experiments are carried out to analyze the prediction results of the SVR algorithm based on four commonly used kernel functions, and the validity and practicability of these kernel functions for the prediction of ship motions are compared.

AB - Short-term prediction of ship motions is of great significance for improving security and efficiency of the offshore operation. Therefore, many prediction models have been proposed by researchers. In recent years, support vector regression algorithm has been proved to be effective to the prediction of ship motions. In this paper, using six degrees of freedom ships motions date collected from real ships, simulation experiments are carried out to analyze the prediction results of the SVR algorithm based on four commonly used kernel functions, and the validity and practicability of these kernel functions for the prediction of ship motions are compared.

KW - kernel function

KW - ship motion

KW - short-term prediction

KW - support vector regression

UR - https://www.scopus.com/pages/publications/85089441270

U2 - 10.1109/ISCID.2019.00021

DO - 10.1109/ISCID.2019.00021

M3 - 会议稿件

AN - SCOPUS:85089441270

T3 - Proceedings - 2019 12th International Symposium on Computational Intelligence and Design, ISCID 2019

SP - 61

EP - 64

BT - Proceedings - 2019 12th International Symposium on Computational Intelligence and Design, ISCID 2019

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 12th International Symposium on Computational Intelligence and Design, ISCID 2019

Y2 - 14 December 2019 through 15 December 2019

ER -

Nie Z, Yuan Y, Xu DI , Shen F. Research on Support Vector Regression Model Based on Different Kernels for Short-term Prediction of Ship Motion. In Proceedings - 2019 12th International Symposium on Computational Intelligence and Design, ISCID 2019. Institute of Electrical and Electronics Engineers Inc. 2019. p. 61-64. 9098246. (Proceedings - 2019 12th International Symposium on Computational Intelligence and Design, ISCID 2019). doi: 10.1109/ISCID.2019.00021

Research on Support Vector Regression Model Based on Different Kernels for Short-term Prediction of Ship Motion

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