计算机工程与应用2017，Vol.53Issue(6)：22-28,7.DOI:10.3778/j.issn.1002-8331.1609-0072
基于趋势函数的空间数据聚类方法
Cluster method for spatial data based on trend function
摘要
Abstract
According to the neglect problem of the importance of attribute data while spatial data clustering and the tendency exploration of spatial feature data, a trend function is established for describing the attribute value change with spatial location. Then, second-order model is constructed by referencing to the variation function. In view of the above, a similarity function integrated spatial distance and attribute difference is built. A treatment scheme regarding of angle tolerance is dis-cussed under stationary hypothesis. Finally, a cluster model named K-Trend is set up with taking trend function as a core. The results show that the K-Trend cluster method has high quality, is seldom affected by sample size, and has moderate time-consuming. All of these features improve the practicability of spatial data cluster.关键词
趋势函数/空间数据/聚类Key words
trend function/spatial data/cluster分类
信息技术与安全科学引用本文复制引用
李建勋,申静静,李维乾,王婉琳..基于趋势函数的空间数据聚类方法[J].计算机工程与应用,2017,53(6):22-28,7.基金项目
"十二五"国家水体污染控制与治理重大专项课题(No.2012ZX07201-006) （No.2012ZX07201-006）
陕西省自然科学基础研究计划项目(No.2014JM9365,No.2015JM5198) （No.2014JM9365,No.2015JM5198）
陕西省教育厅专项科研计划项目(No.16JK1569). （No.16JK1569）
