Fleet route selection prediction problem based on support vector machine

Bulk shipping transport is an important part of ocean transportation. One of the most important aspects for bulk ship owners is to make choices about the ship’s operational area for the next planning period. In this article, based on the Baltic Supermax Index and historical decision data of differen...

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Main Authors: Feng Guan, Xiaopeng Shen, Lan Wu, Yanling Yu, Dongshi Sun, Yanhai Yang
Format: Article
Language:English
Published: SAGE Publishing 2019-04-01
Series:Advances in Mechanical Engineering
Online Access:https://doi.org/10.1177/1687814019836857
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spelling doaj-bc6064428ec44690aee6d00162befb5d2020-11-25T03:51:58ZengSAGE PublishingAdvances in Mechanical Engineering1687-81402019-04-011110.1177/1687814019836857Fleet route selection prediction problem based on support vector machineFeng Guan0Xiaopeng Shen1Lan Wu2Yanling Yu3Dongshi Sun4Yanhai Yang5School of Transportation Engineering, Shenyang Jianzhu University, Shenyang, P.R. ChinaCIECC Overseas Consulting Co., Ltd., Beijing, P.R. ChinaCollege of Automobile and Traffic Engineering, Nanjing Forestry University, Nanjing, P.R. ChinaNidec (Dalian) Limited, Dalian, P.R. ChinaDalian Neusoft University of Information, Dalian, P.R. ChinaSchool of Transportation Engineering, Shenyang Jianzhu University, Shenyang, P.R. ChinaBulk shipping transport is an important part of ocean transportation. One of the most important aspects for bulk ship owners is to make choices about the ship’s operational area for the next planning period. In this article, based on the Baltic Supermax Index and historical decision data of different companies, the support vector machine model is used to predict the dry bulk carrier route selection, which provides a solution to this problem. The numerical results show that the model and the algorithm proposed in the paper can well work and can achieve good precision. Via comparative analysis, we prove that the model we proposed in this article has better performance than some other common methods in the research area. The proposed model would support dry bulk shipping company in route choice so as to balance the profit and potential opportunity when making choice for ships’ route selection.https://doi.org/10.1177/1687814019836857
collection DOAJ
language English
format Article
sources DOAJ
author Feng Guan
Xiaopeng Shen
Lan Wu
Yanling Yu
Dongshi Sun
Yanhai Yang
spellingShingle Feng Guan
Xiaopeng Shen
Lan Wu
Yanling Yu
Dongshi Sun
Yanhai Yang
Fleet route selection prediction problem based on support vector machine
Advances in Mechanical Engineering
author_facet Feng Guan
Xiaopeng Shen
Lan Wu
Yanling Yu
Dongshi Sun
Yanhai Yang
author_sort Feng Guan
title Fleet route selection prediction problem based on support vector machine
title_short Fleet route selection prediction problem based on support vector machine
title_full Fleet route selection prediction problem based on support vector machine
title_fullStr Fleet route selection prediction problem based on support vector machine
title_full_unstemmed Fleet route selection prediction problem based on support vector machine
title_sort fleet route selection prediction problem based on support vector machine
publisher SAGE Publishing
series Advances in Mechanical Engineering
issn 1687-8140
publishDate 2019-04-01
description Bulk shipping transport is an important part of ocean transportation. One of the most important aspects for bulk ship owners is to make choices about the ship’s operational area for the next planning period. In this article, based on the Baltic Supermax Index and historical decision data of different companies, the support vector machine model is used to predict the dry bulk carrier route selection, which provides a solution to this problem. The numerical results show that the model and the algorithm proposed in the paper can well work and can achieve good precision. Via comparative analysis, we prove that the model we proposed in this article has better performance than some other common methods in the research area. The proposed model would support dry bulk shipping company in route choice so as to balance the profit and potential opportunity when making choice for ships’ route selection.
url https://doi.org/10.1177/1687814019836857
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AT yanlingyu fleetrouteselectionpredictionproblembasedonsupportvectormachine
AT dongshisun fleetrouteselectionpredictionproblembasedonsupportvectormachine
AT yanhaiyang fleetrouteselectionpredictionproblembasedonsupportvectormachine
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