Incremental Fuzzy C-Regression Clustering From Streaming Data for Local-Model-Network Identification

In this paper, a new approach to evolving fuzzy model identification from streaming data is given. The structure of the model is given as a local model network in Takagi-Sugeno form, and the partitioning of the input-output space is based on metrics in which these local models are defined as prototy...

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Bibliographic Details
Published in:	IEEE transactions on fuzzy systems Vol. 28; no. 4; pp. 758 - 767
Main Authors:	Blazic, Saso, Skrjanc, Igor
Format:	Journal Article
Language:	English
Published:	New York IEEE 01.04.2020 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Adaptation models Algorithms Clustering Clustering algorithms Computer simulation Data models Evolution Evolving fuzzy model identification fuzzy C-regression clustering incremental clustering Laser range finders Linear programming Mathematical models Parameter identification Partitioning algorithms Prototypes stream data Takagi-Sugeno model
ISSN:	1063-6706, 1941-0034
Online Access:	Get full text
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