dc.contributor.author | Wang, Chunlin | |
dc.contributor.author | Cheng, Xu | |
dc.contributor.author | Chen, Shengyong | |
dc.contributor.author | Li, Guoyuan | |
dc.contributor.author | Zhang, Houxiang | |
dc.date.accessioned | 2019-02-11T08:58:14Z | |
dc.date.available | 2019-02-11T08:58:14Z | |
dc.date.created | 2018-11-09T09:27:19Z | |
dc.date.issued | 2018 | |
dc.identifier.isbn | 978-1-5386-6076-8 | |
dc.identifier.uri | http://hdl.handle.net/11250/2584699 | |
dc.description.abstract | This paper presents a novel method that combines support vector machine (SVM) with sensitivity analysis (SA) to analyze sensor data for ship motion modeling. In order to investigate how each model input contributes to the model's output, the PAWN method which is based on cumulative distribution function (CDF) is used. Considering the limitation of the PAWN method that it cannot be applied to sensor data directly, a surrogate model using SVM is integrated into PAWN method as it has a better solution of non-linearity and high-dimension problem as well as excellent generalization capability. Implementation of whole systematic workflow is elaborated in detail and related experiments are made such as comparison of four distance metric methods, benchmark test and SA of vessel data. The results show the proposed method can be used for analyzing vessel data to seek prime parameters that affect ship motion. | nb_NO |
dc.language.iso | eng | nb_NO |
dc.publisher | Institute of Electrical and Electronics Engineers (IEEE) | nb_NO |
dc.relation.ispartof | Proceedings of 2018 IEEE Int. Conf. on Mechatronics and Automation | |
dc.title | A SVM-based Sensitivity Analysis Approach for Data-Driven Modeling of Ship Motion | nb_NO |
dc.title.alternative | A SVM-based Sensitivity Analysis Approach for Data-Driven Modeling of Ship Motion | nb_NO |
dc.type | Chapter | nb_NO |
dc.description.version | submittedVersion | nb_NO |
dc.source.pagenumber | 803-808 | nb_NO |
dc.identifier.doi | 10.1109/ICMA.2018.8484531 | |
dc.identifier.cristin | 1628584 | |
dc.relation.project | Norges forskningsråd: 237929 | nb_NO |
dc.description.localcode | © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | nb_NO |
cristin.unitcode | 194,64,93,0 | |
cristin.unitname | Institutt for havromsoperasjoner og byggteknikk | |
cristin.ispublished | true | |
cristin.fulltext | preprint | |
cristin.qualitycode | 1 | |