一种用于海底类型聚类的新方法 |
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作者单位: | School of Geodesy and Geomatics,Wuhan University |
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基金项目: | Supported by the National 863 High-Tech Program of China (No. 2007AA12Z326). |
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摘 要: | By using sonar imaging, this paper presents a new algorithm for the clustering of seabed types based on the self-organizing feature maps (SOFM) neural network. The theory as well as data processing is studied in detail. Some valuable conclusions and suggestions are given
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关 键 词: | 海底类型聚类 海洋测量学 SOFM 测量方法 |
收稿时间: | 23 March 2006 |
A new algorithm for clustering of seabed types |
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Authors: | Jianhu Zhao Hongmei Zhang Feihu Ma Juanjuan Li |
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Institution: | School of Geodesy and Geomatics,Wuhan University,129 Luoyu Road,Wuhan 430079,China;School of Geodesy and Geomatics,Wuhan University,129 Luoyu Road,Wuhan 430079,China;School of Geodesy and Geomatics,Wuhan University,129 Luoyu Road,Wuhan 430079,China;School of Geodesy and Geomatics,Wuhan University,129 Luoyu Road,Wuhan 430079,China |
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Abstract: | By using sonar imaging, this paper presents a new algorithm for the clustering of seabed types based on the self-organizing feature maps (SOFM) neural network. The theory as well as data processing is studied in detail. Some valuable conclusions and suggestions are given. |
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Keywords: | sonar image self-organizing feature maps (SOFM) clustering of seabed types |
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