Article | Proceedings of The 59th Conference on Simulation and Modelling (SIMS 59), 26-28 September 2018, Oslo Metropolitan University, Norway | A Data-Driven Sensitivity Analysis Approach for Dynamically Positioned Vessels Link�ping University Electronic Press Conference Proceedings
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Title:
A Data-Driven Sensitivity Analysis Approach for Dynamically Positioned Vessels
Author:
Xu Cheng: School of Computer Science and Technology, Tianjin University of Technology, China / Department of Ocean Operations and Civil Engineering, Norwegian University of Science and Technology, Norway Robert Skulstad: Department of Ocean Operations and Civil Engineering, Norwegian University of Science and Technology, Norway Guoyuan Li: Department of Ocean Operations and Civil Engineering, Norwegian University of Science and Technology, Norway Shengyong Chen: School of Computer Science and Technology, Tianjin University of Technology, China Hans Petter Hildre: Department of Ocean Operations and Civil Engineering, Norwegian University of Science and Technology, Norway Houxiang Zhang: Department of Ocean Operations and Civil Engineering, Norwegian University of Science and Technology, Norway
DOI:
10.3384/ecp18153156
Download:
Full text (pdf)
Year:
2018
Conference:
Proceedings of The 59th Conference on Simulation and Modelling (SIMS 59), 26-28 September 2018, Oslo Metropolitan University, Norway
Issue:
153
Article no.:
022
Pages:
156-161
No. of pages:
6
Publication type:
Abstract and Fulltext
Published:
2018-11-19
ISBN:
978-91-7685-494-5
Series:
Linköping Electronic Conference Proceedings
ISSN (print):
1650-3686
ISSN (online):
1650-3740
Publisher:
Linköping University Electronic Press, Linköpings universitet


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For safety-critical marine operations, the dynamically positioned (DP) vessel should maintain a predetermined heading and position for varying environmental conditions using the thrusters. Studying the effect of each thruster to the capability of DP vessels is significance but challenging. This paper presents a data-driven and variance-based sensitivity analysis (SA) approach that can dig into the ship sensor data to estimate the influence of each thruster for DP operations. Considering high-computational cost of variance-based SA, an Extreme Learning Machine (ELM) -based SA is proposed. To apply the SA to sensor data, an ANN is built and trained on the basis of ship sensor data and then employed as a surrogate model to generate Monte Carlo (MC) samples. A benchmark test shows the correctness of the proposed approach. A case study of SA in DP operation is conducted and the experimental results show that the proposed approach can rank and identify the most sensitive factors. The proposed approach highlights the application of variance-based SA in data-driven modeling for ship intelligence.

Keywords: dynamical positioning, sensitivity analysis, thrust analysis, data-driven modeling

Proceedings of The 59th Conference on Simulation and Modelling (SIMS 59), 26-28 September 2018, Oslo Metropolitan University, Norway

Author:
Xu Cheng, Robert Skulstad, Guoyuan Li, Shengyong Chen, Hans Petter Hildre, Houxiang Zhang
Title:
A Data-Driven Sensitivity Analysis Approach for Dynamically Positioned Vessels
DOI:
http://dx.doi.org/10.3384/ecp18153156
References:
No references available

Proceedings of The 59th Conference on Simulation and Modelling (SIMS 59), 26-28 September 2018, Oslo Metropolitan University, Norway

Author:
Xu Cheng, Robert Skulstad, Guoyuan Li, Shengyong Chen, Hans Petter Hildre, Houxiang Zhang
Title:
A Data-Driven Sensitivity Analysis Approach for Dynamically Positioned Vessels
DOI:
http://dx.doi.org/10.3384/ecp18153156
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Citations:
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Last updated: 2018-9-11