A Case Study of Hierarchical Clustering for Maritime Industry

Fang Han, Hao Wang
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Abstract

. Data in the contemporary world has penetrated into every industry and is increasingly becoming a necessity in enterprises, simultaneously it has also become an important factor of production. Maritime transport is one of the most vital transport systems and maritime big data is attracting increase interest from both the industry and academia. In this paper, we present a case study using hierarchical clustering on a dataset about a vessel’s behavior during operations. We have also produced visually appealing graphs and charts to assist the data analysis.
以海运业层次聚类为例
. 当今世界,数据已经渗透到各行各业,越来越成为企业的必需品,同时也成为重要的生产要素。海上运输是最重要的运输系统之一,海事大数据正引起业界和学术界越来越多的兴趣。在本文中,我们提出了一个案例研究,在一个关于船舶在操作过程中的行为的数据集上使用分层聚类。我们还制作了视觉上吸引人的图形和图表来协助数据分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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