Ghent University Academic Bibliography

Advanced

Clustering-based identification of TS-models : comparison on a groundwater model case study

Hilde Vernieuwe UGent, Bernard De Baets UGent and Niko Verhoest UGent (2004) IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). p.1685-1690
abstract
In this paper, we apply different clustering algorithms for the identification of Takagi-Sugeno models. All of the fuzzy c-means, Gustafson-Kessel, simplified Gustafson-Kessel, Gath and Geva, simplified Gath and Geva, and modified Gath and Geva clustering algorithms try to minimize the same objective function. First, an algorithm for determining the optimal number of clusters is presented. The Takagi-Sugeno models with the optimal number of clusters are then incorporated into a groundwater model, and compared with measurements of the EMSL experiment and the results of a numerical groundwater model.
Please use this url to cite or link to this publication:
author
organization
year
type
conference (proceedingsPaper)
publication status
published
subject
keyword
EQUATION
in
IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)
issue title
2004 IEEE international conference on fuzzy systems, vols 1-3, proceedings
pages
1685 - 1690
publisher
IEEE
place of publication
New York, NY, USA
conference name
2004 Annual IEEE international conference on Fuzzy Systems
conference location
Budapest, Hungary
conference start
2004-07-25
conference end
2004-07-29
Web of Science type
Article
Web of Science id
000224959100292
ISBN
9780780383531
DOI
10.1109/FUZZY.2004.1375434
language
English
UGent publication?
yes
classification
P1
id
404520
handle
http://hdl.handle.net/1854/LU-404520
date created
2008-05-14 16:22:00
date last changed
2018-05-17 14:35:03
@inproceedings{404520,
  abstract     = {In this paper, we apply different clustering algorithms for the identification of Takagi-Sugeno models. All of the fuzzy c-means, Gustafson-Kessel, simplified Gustafson-Kessel, Gath and Geva, simplified Gath and Geva, and modified Gath and Geva clustering algorithms try to minimize the same objective function. First, an algorithm for determining the optimal number of clusters is presented. The Takagi-Sugeno models with the optimal number of clusters are then incorporated into a groundwater model, and compared with measurements of the EMSL experiment and the results of a numerical groundwater model.},
  author       = {Vernieuwe, Hilde and De Baets, Bernard and Verhoest, Niko},
  booktitle    = {IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)},
  isbn         = {9780780383531},
  keyword      = {EQUATION},
  language     = {eng},
  location     = {Budapest, Hungary},
  pages        = {1685--1690},
  publisher    = {IEEE},
  title        = {Clustering-based identification of TS-models : comparison on a groundwater model case study},
  url          = {http://dx.doi.org/10.1109/FUZZY.2004.1375434},
  year         = {2004},
}

Chicago
Vernieuwe, Hilde, Bernard De Baets, and Niko Verhoest. 2004. “Clustering-based Identification of TS-models : Comparison on a Groundwater Model Case Study.” In IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 1685–1690. New York, NY, USA: IEEE.
APA
Vernieuwe, H., De Baets, B., & Verhoest, N. (2004). Clustering-based identification of TS-models : comparison on a groundwater model case study. IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) (pp. 1685–1690). Presented at the 2004 Annual IEEE international conference on Fuzzy Systems, New York, NY, USA: IEEE.
Vancouver
1.
Vernieuwe H, De Baets B, Verhoest N. Clustering-based identification of TS-models : comparison on a groundwater model case study. IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). New York, NY, USA: IEEE; 2004. p. 1685–90.
MLA
Vernieuwe, Hilde, Bernard De Baets, and Niko Verhoest. “Clustering-based Identification of TS-models : Comparison on a Groundwater Model Case Study.” IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). New York, NY, USA: IEEE, 2004. 1685–1690. Print.