摘要
利用WOA05世界大洋数据集1°分辨率、标准分层的气候态平均温、盐场资料,提取一组表征西太平洋海域水声场环境的特征指标。针对海洋水团在温、盐、声等属性特征空间分布的几何结构大多为椭球状的特点,借助一组聚类结果评估函数确定最佳分类区划数目,运用Gustafson-Kessel聚类算法对西太平洋海域水下环境进行分类区划,以便对该海域的声场背景分析和声纳探测提供参考。
Basing on temperature salinity data of the world oceans data sets (WOA05) with 1° resolution and standard layering, a group of characteristic indicators were distilled from underwater acoustic environment of the western Pacific. Considering that the geometric structure of the spacial distribution of temperature salinity sound attribute is mostly hyperelliptic, the western Pacific underwater environment was divided using Gustafson-Kessel clustering algorithm, and the optimal number of clusters was determined by a group of evaluating functions for clustering. The results have practical significance for underwater acoustic field analysis and sonar application.
出处
《热带海洋学报》
CAS
CSCD
北大核心
2008年第5期18-23,共6页
Journal of Tropical Oceanography
基金
中国博士后科学基金项目(2004036012)
关键词
水声环境
特征区划
GK聚类
underwater acoustic environment
characteristic division
G-K clustering