在有序粒度空间理论的基础上,提出基于归一化距离的结构聚类(分类)分析理论和方法研究.首先,提出依距离的一致聚类的概念,给出有序粒度空间的结构聚类特征研究.其次,给出基于归一化距离结构聚类分析完整的理论研究,获得基于归一化距离结构聚类的算法.再给出基于粒度空间的最佳聚类问题研究,提出基于粒度空间的、获取最佳聚类的方法,并且这一方法具备全局最优性质.最后,给出基于归一化距离空间的结构聚类的融合技术的研究,即通过两个归一化距离的交运算获取结构聚类融合的研究方法.这些结论为基于距离的结构聚类(分类)提供一整套理论和方法.
On the basis of the ordered granular space, structural clustering (or classification) analysis is proposed based on normalized metric. Firstly, the concept of consistent clustering according to metric is presented, and the research on consistent clustering characteristic of ordered granular space is given. Secondly, structural clustering analysis theory is given based on normalized metric, and the algorithm to obtain its structural clustering is discussed. Thirdly, the research on the determination of the optimal clustering based on ordered granular space is carried out. A method to obtain the optimal clustering is given, and the method is global optimal. Finally, the fusion technology based on structural clusters of normalized metrics is studied by the intersection operation of two normalized metrics. The conclusions provide a comprehensive theory and methodology on structural clustering (or classification ) analysis based on metric.