Port throughput influence factors based on neighborhood rough sets: An exploratory study

<p><strong>Purpose: </strong>The purpose of this paper is to devise a efficient method for the importance analysis on Port Throughput Influence Factors.</p> <p><strong>Design/methodology/approach: </strong>Neighborhood rough sets is applied to solve the prob...

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Main Authors: Weiping Cui, Lei Huang, Ying Wang
Format: Article
Language:English
Published: OmniaScience 2015-11-01
Series:Journal of Industrial Engineering and Management
Subjects:
Online Access:http://www.jiem.org/index.php/jiem/article/view/1483
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spelling doaj-4399643143174ad08cd0ba541f572a4d2020-11-25T00:09:20ZengOmniaScienceJournal of Industrial Engineering and Management2013-84232013-09532015-11-01851396140810.3926/jiem.1483395Port throughput influence factors based on neighborhood rough sets: An exploratory studyWeiping Cui0Lei Huang1Ying Wang2School of Economics and Management Beijing Jiaotong UniversitySchool of Economics and Management Beijing Jiaotong UniversitySchool of Economics and Management Beijing Jiaotong University<p><strong>Purpose: </strong>The purpose of this paper is to devise a efficient method for the importance analysis on Port Throughput Influence Factors.</p> <p><strong>Design/methodology/approach: </strong>Neighborhood rough sets is applied to solve the problem of selection factors. First the throughput index system is established. Then, we build the attribute reduction model using the updated numerical attribute to reduction algorithm based on neighborhood rough sets. We optimized the algorithm in order to achieve high efficiency performance. Finally, the article do empirical validation using Guangzhou Port throughput and influencing factors’ historical data of year 2000 to 2013.</p> <p><strong>Findings: </strong>Through the model and algorithm, port enterprises can identify the importance of port throughput factors. It can provide support for their decisions.<strong></strong></p> <p><strong>Research limitations: </strong>The empirical data are historical data of year 2000 to 2013. The amount of data is small.<strong></strong></p> <p><strong>Practical implications: </strong>The results provide support for port business investment, decisions and risk control, and also provide assistance for port enterprises’ or other researchers’ throughput forecasting.<strong></strong></p> <p><strong>Originality/value: </strong>In this paper, we establish a throughput index system, and optimize the algorithm for efficiency performance.  <strong></strong></p>http://www.jiem.org/index.php/jiem/article/view/1483Rough Sets, Neighborhood Rough Sets, Port Throughout, Throughout Indicator System
collection DOAJ
language English
format Article
sources DOAJ
author Weiping Cui
Lei Huang
Ying Wang
spellingShingle Weiping Cui
Lei Huang
Ying Wang
Port throughput influence factors based on neighborhood rough sets: An exploratory study
Journal of Industrial Engineering and Management
Rough Sets, Neighborhood Rough Sets, Port Throughout, Throughout Indicator System
author_facet Weiping Cui
Lei Huang
Ying Wang
author_sort Weiping Cui
title Port throughput influence factors based on neighborhood rough sets: An exploratory study
title_short Port throughput influence factors based on neighborhood rough sets: An exploratory study
title_full Port throughput influence factors based on neighborhood rough sets: An exploratory study
title_fullStr Port throughput influence factors based on neighborhood rough sets: An exploratory study
title_full_unstemmed Port throughput influence factors based on neighborhood rough sets: An exploratory study
title_sort port throughput influence factors based on neighborhood rough sets: an exploratory study
publisher OmniaScience
series Journal of Industrial Engineering and Management
issn 2013-8423
2013-0953
publishDate 2015-11-01
description <p><strong>Purpose: </strong>The purpose of this paper is to devise a efficient method for the importance analysis on Port Throughput Influence Factors.</p> <p><strong>Design/methodology/approach: </strong>Neighborhood rough sets is applied to solve the problem of selection factors. First the throughput index system is established. Then, we build the attribute reduction model using the updated numerical attribute to reduction algorithm based on neighborhood rough sets. We optimized the algorithm in order to achieve high efficiency performance. Finally, the article do empirical validation using Guangzhou Port throughput and influencing factors’ historical data of year 2000 to 2013.</p> <p><strong>Findings: </strong>Through the model and algorithm, port enterprises can identify the importance of port throughput factors. It can provide support for their decisions.<strong></strong></p> <p><strong>Research limitations: </strong>The empirical data are historical data of year 2000 to 2013. The amount of data is small.<strong></strong></p> <p><strong>Practical implications: </strong>The results provide support for port business investment, decisions and risk control, and also provide assistance for port enterprises’ or other researchers’ throughput forecasting.<strong></strong></p> <p><strong>Originality/value: </strong>In this paper, we establish a throughput index system, and optimize the algorithm for efficiency performance.  <strong></strong></p>
topic Rough Sets, Neighborhood Rough Sets, Port Throughout, Throughout Indicator System
url http://www.jiem.org/index.php/jiem/article/view/1483
work_keys_str_mv AT weipingcui portthroughputinfluencefactorsbasedonneighborhoodroughsetsanexploratorystudy
AT leihuang portthroughputinfluencefactorsbasedonneighborhoodroughsetsanexploratorystudy
AT yingwang portthroughputinfluencefactorsbasedonneighborhoodroughsetsanexploratorystudy
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