Full Content is available to subscribers

Subscribe/Learn More  >

Simplifying Neural Network Based Model for Ship Motion Prediction: A Comparative Study of Sensitivity Analysis

[+] Author Affiliations
Xu Cheng, Shengyong Chen, Chen Diao, Mengna Liu

Tianjin University of Technology, Tianjin, China

Guoyuan Li, Houxiang Zhang

Norwegian University of Science and Technology, Aalesund, Norway

Paper No. OMAE2017-61474, pp. V001T01A016; 8 pages
  • ASME 2017 36th International Conference on Ocean, Offshore and Arctic Engineering
  • Volume 1: Offshore Technology
  • Trondheim, Norway, June 25–30, 2017
  • Conference Sponsors: Ocean, Offshore and Arctic Engineering Division
  • ISBN: 978-0-7918-5763-2
  • Copyright © 2017 by ASME


This paper presents a comparative study of sensitivity analysis (SA) and simplification on artificial neural network (ANN) based model used for ship motion prediction. Considering traditional structural complexity of ANN usually results in slow convergence, SA, as an efficient tool for correlation analysis, can help to reconstruct the ANN model for ship motion prediction. An ANN-Garson method and an ANN-EFAST method are proposed, both of which utilize the ANN for modeling but select the input parameters in a local and a global fashion, respectively. Through the benchmark tests, ANN-EFAST exhibits superior performance in both linear and nonlinear systems. Further test on ANN-EFAST via a case study of ship heading prediction shows its cost-effective and timely in compacting the ANN based prediction model.

Copyright © 2017 by ASME



Interactive Graphics


Country-Specific Mortality and Growth Failure in Infancy and Yound Children and Association With Material Stature

Use interactive graphics and maps to view and sort country-specific infant and early dhildhood mortality and growth failure data and their association with maternal

Citing articles are presented as examples only. In non-demo SCM6 implementation, integration with CrossRef’s "Cited By" API will populate this tab (http://www.crossref.org/citedby.html).

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In