Volume 1, Issue 1, January 2008, Pages 60 - 76
From Fuzzy Clustering to a Fuzzy Rule-Based Classification Model
- Enrico Zio, Piero Baraldi, Irina Crenguta Popescu
- Corresponding Author
- Enrico Zio
Available Online 10 February 2008.
- https://doi.org/10.2991/ijcis.2008.1.1.5How to use a DOI?
- 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.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - JOUR AU - Enrico Zio AU - Piero Baraldi AU - Irina Crenguta Popescu PY - 2008 DA - 2008/02 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 - https://doi.org/10.2991/ijcis.2008.1.1.5 ID - Zio2008 ER -