Elucidating families of ship designs using clustering algorithms

Ted Jaspers, Austin Kana

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

Abstract

This paper proposes a method to elucidate families of ship designs generated by the TU Delft packing approach using data clustering algorithms. The authors explore whether commonly used data science techniques can extract new information from the existing data. To test this hypothesis this paper applies data clustering algorithms to a test case of layouts of a Mine Counter Measures Vessel (MCMV) generated by the packing approach. Results look to improve the understanding of the multidimensional structure of the data, as well as to improve the comprehension and visualization of the complex interactions between the design and performance space.
Original languageEnglish
Title of host publicationProceedings of the 16th International Conference on Computer and IT Applications in the Maritime Industries COMPIT'17
EditorsV. Bertram
Place of PublicationHamburg
PublisherTechnische Universität Hamburg-Harburg
Pages474-485
ISBN (Print)978-3-89220-701-6
Publication statusPublished - 2017
Event16th Conference on Computer and IT Applications in the Maritime Industries - Cardiff, United Kingdom
Duration: 15 May 201717 May 2017
Conference number: 16

Conference

Conference16th Conference on Computer and IT Applications in the Maritime Industries
Abbreviated titleCOMPIT,17
CountryUnited Kingdom
CityCardiff
Period15/05/1717/05/17

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