时变空间模式聚类算法的性能

B. Pinkowski
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引用次数: 3

摘要

采用一种适用于时间分布点的单链接聚类算法(SLOT),从与时间参数相关的共面点中恢复聚类。聚类的数量和形状决定了算法的可分性,从而决定了算法的有效性。仿真实验中的性能也取决于记录聚类点的概率。如果槽链路处于一定的限制距离内,则它们会在不同的时间被观测到,当可探测性较低时,距离参数变得至关重要。与其他算法进行性能比较,并在基于规则的专家系统的背景下提出结果,用于解决涉及时间依赖空间模式的聚类分析的问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Performance of clustering algorithms on time-dependent spatial patterns
A single linkage clustering algorithm adapted for points distributed over time (SLOT) is used to recover clusters from coplanar points associated with time parameters. Cluster number and shape determine separability and hence effectiveness of the algorithm. Performance in simulation experiments also depended on the probability of recording cluster points. SLOT links points observed at different times if they are within some limiting distance, and the distance parameter becomes critical when detectability is low. Performance comparisons are made with other algorithms, and results are presented in the context of a rule-based expert system for solving problems involving cluster analysis of time-dependent spatial patterns.
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