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...
Main Authors: | , , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
SAGE Publishing
2019-04-01
|
Series: | Advances in Mechanical Engineering |
Online Access: | https://doi.org/10.1177/1687814019836857 |
id |
doaj-bc6064428ec44690aee6d00162befb5d |
---|---|
record_format |
Article |
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 |
work_keys_str_mv |
AT fengguan fleetrouteselectionpredictionproblembasedonsupportvectormachine AT xiaopengshen fleetrouteselectionpredictionproblembasedonsupportvectormachine AT lanwu fleetrouteselectionpredictionproblembasedonsupportvectormachine AT yanlingyu fleetrouteselectionpredictionproblembasedonsupportvectormachine AT dongshisun fleetrouteselectionpredictionproblembasedonsupportvectormachine AT yanhaiyang fleetrouteselectionpredictionproblembasedonsupportvectormachine |
_version_ |
1724485258424877056 |