Ocean Front Reconstruction Method Based on K-Means Algorithm Iterative Hierarchical Clustering Sound Speed Profile

As one of the most common mesoscale phenomena in the ocean, the ocean front is defined as a narrow transition zone between two water masses with obviously different properties. In this study, we proposed an ocean front reconstruction method based on the K-means algorithm iterative hierarchical clust...

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Autores principales:	Yuyao Liu, Wei Chen, Yu Chen, Wen Chen, Lina Ma, Zhou Meng
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	ocean front K-means algorithm reconstruction iterative hierarchical clustering transmission loss Naval architecture. Shipbuilding. Marine engineering VM1-989 Oceanography GC1-1581
Acceso en línea:	https://doaj.org/article/498c7a582bbb4a6fa1d7e52f916d9707
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id	oai:doaj.org-article:498c7a582bbb4a6fa1d7e52f916d9707
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spelling	oai:doaj.org-article:498c7a582bbb4a6fa1d7e52f916d97072021-11-25T18:04:34ZOcean Front Reconstruction Method Based on K-Means Algorithm Iterative Hierarchical Clustering Sound Speed Profile10.3390/jmse91112332077-1312https://doaj.org/article/498c7a582bbb4a6fa1d7e52f916d97072021-11-01T00:00:00Zhttps://www.mdpi.com/2077-1312/9/11/1233https://doaj.org/toc/2077-1312As one of the most common mesoscale phenomena in the ocean, the ocean front is defined as a narrow transition zone between two water masses with obviously different properties. In this study, we proposed an ocean front reconstruction method based on the K-means algorithm iterative hierarchical clustering sound speed profile (SSP). This method constructed the frontal zone from the perspective of SSP. Meanwhile, considering that acoustic ray tracing is a very sensitive tool for detecting the location of ocean fronts because of the strong dependence of the transmission loss (TL) on SSP structure, this paper verified the feasibility of the method from the perspective of the TL calculation. Compared with other existing methods, this method has the key step of iterative hierarchical clustering according to the accuracy of clustering results. The results of iterative hierarchical clustering of the SSP can reconstruct the ocean front. Using this method, we reconstructed the ocean front in the Gulf Stream-related sea area and obtained the three-dimensional structure of the Gulf Stream front (GSF). The three-dimensional structure was divided into seven layers in the depth range of 0–1000 m. Iterative hierarchical clustering SSP by K-means algorithm provides a new method for judging the frontal zone and reconstructing the geometric model of the ocean front in different depth ranges.Yuyao LiuWei ChenYu ChenWen ChenLina MaZhou MengMDPI AGarticleocean frontK-means algorithmreconstructioniterative hierarchical clusteringtransmission lossNaval architecture. Shipbuilding. Marine engineeringVM1-989OceanographyGC1-1581ENJournal of Marine Science and Engineering, Vol 9, Iss 1233, p 1233 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	ocean front K-means algorithm reconstruction iterative hierarchical clustering transmission loss Naval architecture. Shipbuilding. Marine engineering VM1-989 Oceanography GC1-1581
spellingShingle	ocean front K-means algorithm reconstruction iterative hierarchical clustering transmission loss Naval architecture. Shipbuilding. Marine engineering VM1-989 Oceanography GC1-1581 Yuyao Liu Wei Chen Yu Chen Wen Chen Lina Ma Zhou Meng Ocean Front Reconstruction Method Based on K-Means Algorithm Iterative Hierarchical Clustering Sound Speed Profile
description	As one of the most common mesoscale phenomena in the ocean, the ocean front is defined as a narrow transition zone between two water masses with obviously different properties. In this study, we proposed an ocean front reconstruction method based on the K-means algorithm iterative hierarchical clustering sound speed profile (SSP). This method constructed the frontal zone from the perspective of SSP. Meanwhile, considering that acoustic ray tracing is a very sensitive tool for detecting the location of ocean fronts because of the strong dependence of the transmission loss (TL) on SSP structure, this paper verified the feasibility of the method from the perspective of the TL calculation. Compared with other existing methods, this method has the key step of iterative hierarchical clustering according to the accuracy of clustering results. The results of iterative hierarchical clustering of the SSP can reconstruct the ocean front. Using this method, we reconstructed the ocean front in the Gulf Stream-related sea area and obtained the three-dimensional structure of the Gulf Stream front (GSF). The three-dimensional structure was divided into seven layers in the depth range of 0–1000 m. Iterative hierarchical clustering SSP by K-means algorithm provides a new method for judging the frontal zone and reconstructing the geometric model of the ocean front in different depth ranges.
format	article
author	Yuyao Liu Wei Chen Yu Chen Wen Chen Lina Ma Zhou Meng
author_facet	Yuyao Liu Wei Chen Yu Chen Wen Chen Lina Ma Zhou Meng
author_sort	Yuyao Liu
title	Ocean Front Reconstruction Method Based on K-Means Algorithm Iterative Hierarchical Clustering Sound Speed Profile
title_short	Ocean Front Reconstruction Method Based on K-Means Algorithm Iterative Hierarchical Clustering Sound Speed Profile
title_full	Ocean Front Reconstruction Method Based on K-Means Algorithm Iterative Hierarchical Clustering Sound Speed Profile
title_fullStr	Ocean Front Reconstruction Method Based on K-Means Algorithm Iterative Hierarchical Clustering Sound Speed Profile
title_full_unstemmed	Ocean Front Reconstruction Method Based on K-Means Algorithm Iterative Hierarchical Clustering Sound Speed Profile
title_sort	ocean front reconstruction method based on k-means algorithm iterative hierarchical clustering sound speed profile
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/498c7a582bbb4a6fa1d7e52f916d9707
work_keys_str_mv	AT yuyaoliu oceanfrontreconstructionmethodbasedonkmeansalgorithmiterativehierarchicalclusteringsoundspeedprofile AT weichen oceanfrontreconstructionmethodbasedonkmeansalgorithmiterativehierarchicalclusteringsoundspeedprofile AT yuchen oceanfrontreconstructionmethodbasedonkmeansalgorithmiterativehierarchicalclusteringsoundspeedprofile AT wenchen oceanfrontreconstructionmethodbasedonkmeansalgorithmiterativehierarchicalclusteringsoundspeedprofile AT linama oceanfrontreconstructionmethodbasedonkmeansalgorithmiterativehierarchicalclusteringsoundspeedprofile AT zhoumeng oceanfrontreconstructionmethodbasedonkmeansalgorithmiterativehierarchicalclusteringsoundspeedprofile
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Ocean Front Reconstruction Method Based on K-Means Algorithm Iterative Hierarchical Clustering Sound Speed Profile

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