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Fuzzy Model Identification Based on Cluster Estimation

Chiu, Stephen L.·1994·Journal of Intelligent & Fuzzy Systems

Abstract

We present an efficient method for estimating cluster centers of numerical data. This method can be used to determine the number of clusters and their initial values for initializing iterative optimization-based clustering algorithms such as fuzzy C-means. Here we use the cluster estimation method as the basis of a fast and robust algorithm for identifying fuzzy models. A benchmark problem involving the prediction of a chaotic time series shows this model identification method compares favorably with other, more computationally intensive methods. We also illustrate an application of this method in modeling the relationship between automobile trips and demographic factors.

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Metadata

Authors
Chiu, S. L.
Venue
Journal of Intelligent & Fuzzy Systems
Published
1994-08
Volume
2
Issue
3
Pages
267-278
ISSN
  • 1064-1246 (ISSN-L)
  • 1875-8967
OpenAlex
W1570834090
Cited by
2,782
References
0
FWCI
7.13
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Fuzzy Model Identification Based on Cluster Estimation. https://app.cochat.ai/papers/10.3233/ifs-1994-2306
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Chiu, S. L. (1994). Fuzzy Model Identification Based on Cluster Estimation. Journal of Intelligent & Fuzzy Systems. https://doi.org/10.3233/ifs-1994-2306

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.