کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
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4534652 | 1626357 | 2013 | 10 صفحه PDF | دانلود رایگان |
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 SOM analysis. SOM 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.
► The self-organizing map analysis is compared with the cluster analysis methods.
► The EOF is used to reduce the data dimension and data noises.
► The SOM is the most insensitive to the cut-off EOF mode number.
Journal: Deep Sea Research Part I: Oceanographic Research Papers - Volume 73, March 2013, Pages 117–126