Skip to main content
SpringerLink
Log in

Application of Support Vector Machine in the Decision-Making of Maneuvering

  • Conference paper
Algorithms and Architectures for Parallel Processing (ICA3PP 2014)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8631))

  • 2597 Accesses

Abstract

To get the best course and speed navigating in stormy waves, establish the sea-keeping assessment model based on Support Vector Machine method, verify the accuracy of the model with sea-keeping estimation equation, and finally apply it in decision making of maneuvering. It turns out that the assessment model works well. The conclusions provide references for maneuvering in stormy waves.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Li, S.Z., Wang, F.W., Liu, Q., Qi, Z.: SeakeepingEvaluation Based on BP Neural Network. Journal of Dalian Maritime University 38(1), 15–17 (2012) (in Chinese)

    Google Scholar 

  2. Wu, Z.Q.: TheResearch on the Evaluation for Investment Risk of Freeway Project Based on Support Vector Machine. Changsha Technical University (2009) (in Chinese)

    Google Scholar 

  3. Ai, N., Wu, Z.W., Ren, J.H.: Support Vector Machine and Artificial Neural Network. Journal of Shandong University of Technology 19(5), 45–49 (2005) (in Chinese)

    Google Scholar 

  4. Pan, X., Yang, R.Y.: The Research on Neural Networks with Enhanced Generalization and Support Vector Machine. Journal of Anqing Teachers College 13(1), 32–36 (2007) (in Chinese)

    Google Scholar 

  5. Bai, P., Zhang, X.B.: Theory of Support Vector Mechanism and the Examples of Engineering Application. Xi’an Electronic and Technology University Press (2008) (in Chinese)

    Google Scholar 

  6. Chang, Z., Lu, J.: Application of Support Vector Machine in the Evaluation of Dry Ports Investment Risk. Journal of Dalian Maritime University 38(2), 48–51 (2012) (in Chinese)

    Google Scholar 

  7. Xiong, W.H., Mao, X.F., Li, Y.J.: Review on Evaluation Methods and Criteria for Sea-keeping of Ships. Ship & Ocean Engineering 36(4), 43–44 (2007) (in Chinese)

    Google Scholar 

  8. Vapnik, V.: An Overview of Statistical Learning Theory. IEEE Transaction on Neural Networks 10(5), 988–999 (1999)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Navigation College, Dalian Maritime University, Dalian, 116026, China

    Zhuang Qi, Hanbang Song & Xinyu Zhang

  2. Transportation Management College, Dalian Maritime University, Dalian, 116026, China

    Zheng Chang

Authors
  1. Zhuang Qi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Zheng Chang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Hanbang Song
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Xinyu Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Department of Computer Science, Illinois Institute of Technology, 60616-3793, Chicago, IL, USA

    Xian-he Sun

  2. School of Computer Science and Technology, Dalian Maritime University, 1 Linghai Road, 116026, Dalian, China

    Wenyu Qu

  3. SEECS, University of Ottawa, 8, King Edward Ave, K1N 6N5, Ottawa, ON, Canada

    Ivan Stojmenovic

  4. Deakin University, 221 Burwood Highway, 3125, Burwood, VIC, Australia

    Wanlei Zhou

  5. Dalian Maritime University, NO.1 Linhai Road Dailian, 116026, China

    Zhiyang Li

  6. BeiHang University, XueYuan Road No.37, HaiDian District, Beijing, China

    Hua Guo

  7. University of Bradford, BD7 1DP, Bradford, West Yorkshire, United Kingdom

    Geyong Min

  8. Dalian Maritime University, NO.1 Linhai Road Dailian, China, 116026

    Tingting Yang

  9. Computer Network Information Center, Chinese Academy of Sciences, 100190, Beijing, China

    Yulei Wu

  10. Shandong University, 27 Shanda Nanlu, 250100, Jinan City, Shandong Province, China

    Lei Liu

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this paper

Cite this paper

Qi, Z., Chang, Z., Song, H., Zhang, X. (2014). Application of Support Vector Machine in the Decision-Making of Maneuvering. In: Sun, Xh., et al. Algorithms and Architectures for Parallel Processing. ICA3PP 2014. Lecture Notes in Computer Science, vol 8631. Springer, Cham. https://doi.org/10.1007/978-3-319-11194-0_27

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-11194-0_27

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-11193-3

  • Online ISBN: 978-3-319-11194-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation