%0 Journal Article
%T Application of SOFM neural network for analyzing non-spatial attributes<br>SOFM神经网络在处理非空间属性中的应用
%A SUN Zhi-wei
%A ZHAO Zheng
%A <br>孙志伟
%A 赵政
%J 计算机应用
%D 2006
%I 
%X Because of high dimension characteristic of non-spatial attributes, the difficulties in operation are how to set parameters for these attributes. When using general spatial clustering algorithm, the difficulties are how to judge which dimensions play main role and affect cluster result. Based on the research of those problems, a method for analyzing non-spatial attributes was proposed. First, Self-Organizing Feature Map (SOFM) was adopted to choose some dimensions, and used to cluster the dense non-spatial attributes on these dimensions. Then the cluster of non-spatial attributes and that of spatial attributes were merged.
%K clustering algorithm
%K high-dimension
%K neural network
%K Self-Organizing Feature Map(SOFM)
%K constraint<br>聚类算法
%K 高维
%K 神经网络
%K 自组织特征映射
%K 约束
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=831E194C147C78FAAFCC50BC7ADD1732&aid=245BADA010F37562&yid=37904DC365DD7266&vid=96C778EE049EE47D&iid=708DD6B15D2464E8&sid=30D12647FBC8A758&eid=E8DEC1A5DEE63AD8&journal_id=1001-9081&journal_name=计算机应用&referenced_num=0&reference_num=7