| DOI | Trouver le DOI : https://doi.org/10.1109/OCEANS55160.2024.10754101 |
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| Auteur | Rechercher : Piercey, Caitlin1; Rechercher : Hamilton, Matthew1; Rechercher : Veitch, Brian1; Rechercher : Barnes, Joshua2Identifiant ORCID : https://orcid.org/0000-0002-3371-1082; Rechercher : Jiang, Xianta1 |
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| Affiliation | - Memorial University of Newfoundland
- Conseil national de recherches Canada. Génie océanique, côtier et fluvial
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| Bailleur de fonds | Rechercher : National Research Council Canada |
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| Format | Texte, Article |
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| Conférence | OCEANS 2024 - Halifax, September 23-26, 2024, Halifax, Nova Scotia, Canada |
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| Sujet | decision support systems; oceans; clustering algorithms; predictive models; genetics; data models; fuels; data mining; marine vehicles; optimization |
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| Résumé | In this paper, we propose a hybrid clustering algorithm based on hierarchical clustering in combination with string clustering, similar to that used in clustering genetic sequences, to extract clusters of operational activities from ship data. After extracting clusters (n=9), the distribution and summary statistics of each cluster are compared to Canadian Coast Guard provided operational definitions to obtain context from the clusters. The clustered data is used as the input to a fuel flow prediction model, which will in turn form the basis of an on-board decision support system for marine vessels with the goal of reducing fuel consumption. Finally, we compare the results of fuel flow predictions with models trained on a) different clusters and b) the full dataset, to determine the usefulness of these clusters in improving the performance of a fuel-optimization decision support system for on-board marine vessel use. |
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| Date de publication | 2024-09-23 |
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| Maison d’édition | IEEE |
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| Dans | |
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| Série | |
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| Langue | anglais |
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| Publications évaluées par des pairs | Oui |
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| Exporter la notice | Exporter en format RIS |
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| Signaler une correction | Signaler une correction (s'ouvre dans un nouvel onglet) |
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| Identificateur de l’enregistrement | 993cc75d-3b17-4c69-b281-c35c1115becb |
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| Enregistrement créé | 2026-04-08 |
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| Enregistrement modifié | 2026-05-20 |
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