期刊
DEEP-SEA RESEARCH PART I-OCEANOGRAPHIC RESEARCH PAPERS
卷 73, 期 -, 页码 117-126出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.dsr.2012.12.001
关键词
Cluster analysis; Ward method; K-means method; SOM; EOF
类别
资金
- Ministry of Education, Culture, Sports, Science, and Technology of Japan [20540429]
- Grants-in-Aid for Scientific Research [20540429] Funding Source: KAKEN
Classification of ocean data maps is important for analysis of ocean data. Here, we compare self-organizing map (SOM) analysis with cluster methods such as the Ward method and K-means method. The HF (high-frequency) radar surface current data east of Okinawa Island, Japan were used for the comparison. There are two typical current patterns in the observation area: a strong southward current and a clockwise eddy-like current pattern. The classification results by the Ward method was similar to that by the SUM analysis. SUM analysis was insensitive to the cut-off empirical orthogonal function (EOF) mode number for reducing the data dimensions and noise, while the K-means method was the most sensitive to the EOF mode number. (c) 2012 Elsevier Ltd. All rights reserved.
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