Document Type
Article
Publication Date
5-1-2011
Publication Title
Annals of Nuclear Energy
Volume
38
Issue
5
First Page
1161
Keywords
Bagging, BWR nuclear power plant, Classification, Ensemble, Fuzzy C-means (FCM) clustering, Transient identification
Last Page
1171
Abstract
This paper presents an ensemble-based scheme for nuclear transient identification. The approach adopted to construct the ensemble of classifiers is bagging; the novelty consists in using supervised fuzzy C-means (FCM) classifiers as base classifiers of the ensemble. The performance of the proposed classification scheme has been verified by comparison with a single supervised, evolutionary-optimized FCM classifier with respect of the task of classifying artificial datasets. The results obtained indicate that in the cases of datasets of large or very small sizes and/or complex decision boundaries, the bagging ensembles can improve classification accuracy. Then, the approach has been applied to the identification of simulated transients in the feedwater system of a boiling water reactor (BWR).
DOI
10.1016/j.anucene.2010.12.009
ISSN
03064549
Recommended Citation
Baraldi, Piero; Razavi-Far, Roozbeh; and Zio, Enrico. (2011). Bagged ensemble of Fuzzy C-Means classifiers for nuclear transient identification. Annals of Nuclear Energy, 38 (5), 1161-1171.
https://scholar.uwindsor.ca/electricalengpub/175
