Clustering Analysis of Main Vessel Traffic Flow Observation Lines along Yangtze River

Yan Fei Tian; Xiao Yang Wei

doi:10.4028/www.scientific.net/AMM.744-746.1792

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 744-746Clustering Analysis of Main Vessel Traffic Flow...

Clustering Analysis of Main Vessel Traffic Flow Observation Lines along Yangtze River

Abstract:

For the reasonable grouping of the 16 vessel traffic flow observation lines along Yangtze River to compare them with each other, essential data of nearly 6 years taken with the mean relative growth rate of traffic flow over the yearly same period set as clustering index, the clustering of the 16 vessel traffic flow observation lines was realized on MATLAB in accordance with the set index based on the basic principle and processes of Agglomerative Hierarchical Clustering Method, which indicated that the observation lines can be divided into 3 classes, and particularly Jiujiang took an exclusive class obviously different from the other two. This work would provide scientific basis of grouping the observation lines in order to reflect shipping economy of the regions where the observation lines are located and to provide reference for management decisions.

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Periodical:

Applied Mechanics and Materials (Volumes 744-746)

Pages:

1792-1796

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.744-746.1792

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Cite this paper

Online since:

March 2015

Authors:

Yan Fei Tian*, Xiao Yang Wei

Keywords:

Agglomerative Hierarchical Clustering Method, Classification, Traffic Engineering, Vessel Traffic Flow Observation Lines

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* - Corresponding Author

References

[1] ZHENG B, CHEN J B, JIN Y X. Analysis of Marine Traffic Flow Characteristics Based on Data Mining[J]. Navigation OF China, 2009, 32(1): 30-63. (In Chinese).

Google Scholar

[2] LI T. The Application of Clustering Analysis in Traffic Flow Time Series Data Mining[D]. Beijing Jiaotong University, 2007. 12. (In Chinese).

Google Scholar

[3] ZHANG X. Study on Hierarchical Clustering Algorithm[D]. JiangXi University of Science and Technology, 2008. 12. (In Chinese).

Google Scholar

[4] WANG F. Analysis and Improvement of Traditional Clustering Methods[D]. Central South University, 2007. 12. (In Chinese).

Google Scholar

[5] CAO G H, JIAO Y Y, CHENG Q. Research on Tag Cluster Based on Hierarchical Agglomerative Clustering Algorithm[J]. New Technology of Library and Information Service, 2008(4): 23-28. (In Chinese).

Google Scholar

[6] XU Y H, WU Y Y. Analysis of ATM Transactions Based on Clustering Method[J]. FINANCIAL COMPUTER OF HUANAN, 2006(1): 56-58. (In Chinese).

Google Scholar

[7] ZHANG S W, LEI Y J, FENG Y Q. Application of MATLAB in Time Series Analysis[M]. XiDian University Press, 2007. 4. (In Chinese).

Google Scholar

[8] Information on http: /www. cjmsa. gov. cn/9/368/2/29/301/. (In Chinese).

Google Scholar