CBCG: A Clustering Algorithm Based on Bidirectional Conical Information Granularity

In this article, we propose a novel center-based clustering algorithm based on bidirectional conical information granularity. The main purpose is to fully absorb the semantic information of the ordinal relationship between objects to improve the performance of central clustering in identifying inter...

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Veröffentlicht in:	IEEE transactions on fuzzy systems Jg. 32; H. 8; S. 4388 - 4400
Hauptverfasser:	Yu, Bin, Zheng, Zijian, Cai, Mingjie, Pedrycz, Witold, Xu, Zeshui
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	IEEE 01.08.2024
Schlagworte:	<named-content xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" content-type="math" xlink:type="simple"> <inline-formula> <tex-math notation="LaTeX"> k</tex-math> </inline-formula> </named-content>-bidirectional conical information granularity Bidirectional conical information granularity center-based clustering Clustering algorithms Clustering methods Data mining Data models fuzzy importance degree (FID) Fuzzy systems Granular computing Semantics two-step division
ISSN:	1063-6706, 1941-0034
Online-Zugang:	Volltext
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