From Fuzzy Clustering to a Fuzzy Rule-Based Classification Model

DOI

10.2991/ijcis.2008.1.1.5How to use a DOI?

Abstract

The applicability in practice of a diagnostic tool is strongly related to the physical transparency of the un- derlying models, for the interpretation of the relationships between the involved variables and for direct model inspection and validation. In this work, a methodology is developed for transforming an opaque, fuzzy clustering-based classification model into a fuzzy logic model based on transparent linguistic rules. These are obtained by cluster projection with appropriate coverage and distinguishability constraints onto the fuzzy input partitioning interface. The methodological approach is applied to a diagnostic task con- cerning the classification of simulated faults in the feedwater system of a nuclear Boiling Water Reactor.

Copyright

© 2008, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - JOUR
AU  - Enrico Zio
AU  - Piero Baraldi
AU  - Irina Crenguta Popescu
PY  - 2008
DA  - 2008/01/01
TI  - From Fuzzy Clustering to a Fuzzy Rule-Based Classification Model
JO  - International Journal of Computational Intelligence Systems
SP  - 60
EP  - 76
VL  - 1
IS  - 1
SN  - 1875-6883
UR  - https://doi.org/10.2991/ijcis.2008.1.1.5
DO  - 10.2991/ijcis.2008.1.1.5
ID  - Zio2008
ER  -