A K-Means Clustering Algorithm to Determine Representative Operational Profiles of a Ship Using AIS Data

Defining the appropriate functional requirements in the early ship design stage is important in order that costs that are caused by the over- or under-specified functional capabilities do not increase. This paper presents a K-means clustering algorithm for the determination of functional requirement...

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Bibliographic Details
Published in:Journal of marine science and engineering 2022-09, Vol.10 (9), p.1245
Main Authors: Park, Jongseo, Choi, Minjoo
Format: Article
Language:English
Subjects:
Algorithms
automatic identification system (AIS)
Case studies
Cluster analysis
Clustering
Data mining
Decision making
Design
Emissions
K-means clustering algorithm
Naval engineering
operational profile
Ship design
Ships
Vector quantization
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Summary:Defining the appropriate functional requirements in the early ship design stage is important in order that costs that are caused by the over- or under-specified functional capabilities do not increase. This paper presents a K-means clustering algorithm for the determination of functional requirements. It uses automatic identification system (AIS) data from a reference ship to determine the representative operational profiles, which can support decision-makers in defining the functional requirements of ships that will be performing similar missions as those of the reference ship. In a case study, we used this method as part of a ship design project, in which the functional requirements of a battery-only electric ship are defined using AIS data from a reference ship. Results indicate that the cost can be reduced by determining the functional requirements using the proposed method.
ISSN:2077-1312
2077-1312
DOI:10.3390/jmse10091245