Linear Fuzzy Information-Granule-Based Fuzzy C-Means Algorithm for Clustering Time Series

This article aims to design a trend-oriented-granulation-based fuzzy <inline-formula> <tex-math notation="LaTeX">C </tex-math></inline-formula>-means (FCM) algorithm that can cluster a group of time series at an abstract (granular) level. To achieve a better trend-o...

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Bibliographic Details
Published in:	IEEE transactions on cybernetics Vol. 53; no. 12; pp. 7622 - 7634
Main Authors:	Yang, Zonglin, Jiang, Shurong, Yu, Fusheng, Pedrycz, Witold, Yang, Huilin, Hao, Yadong
Format:	Journal Article
Language:	English
Published:	Piscataway IEEE 01.12.2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Algorithms Clustering Clustering algorithms Dynamic time warping (DTW) fuzzy C-means (FCM) Granular materials Granulation Heuristic algorithms Iterative methods linear fuzzy information granule (LFIG) l₁ trend filtering Merging Prototypes Segments Time measurement Time series Time series analysis time-series clustering Trends
ISSN:	2168-2267, 2168-2275, 2168-2275
Online Access:	Get full text
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