Fuzzy K-means clustering models for triangular fuzzy time trajectories

被引：5

作者：

Coppi R. ^{[1
]}

D'Urso P. ^{[1
]}

机构：

[1] Dipartimento di Statistica, Probabilità e Statistiche Applicate, Università degli Studi di Roma La Sapienza, 00185 Roma

来源：

Statistical Methods and Applications | 2002年 / 11卷 / 1期

关键词：

Cross sectional and/or longitudinal double fuzzy clustering; Fuzzy time array; Fuzzy time trajectory; Informational support; Triangular membership function;

D O I：

10.1007/BF02511444

中图分类号：

学科分类号：

摘要：

We focus our attention on the classification of fuzzy time trajectories with triangular membership function, described by a given set of individuals. To this purpose, we adopt a fully informational approach, explicitly recognizing the informational nature shared by the ingredients of the classification procedure: the observed data (Empirical Information) and the classification model (Theoretical Information). In particular, by supposing that the informational paradigm has a fuzzy nature, we suggest three fuzzy clustering models allowing the classification of the triangular fuzzy time trajectories, based on the analysis of the cross sectional and/or longitudinal characteristics of their components (centers and spreads). Two applicative examples are illustrated. © Springer-Verlag 2002.

引用

页码：21 / 40

页数：19

共 17 条

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