A Case Study of Hierarchical Clustering for Maritime Industry

Fang HAN, Hao WANG

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.

Keywords


Big data, Machine learning, Hierarchical clustering


DOI
10.12783/dtmse/amsee2017/14300

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