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Journal articles
Bagged ensemble of Fuzzy C-Means classifiers for nuclear transient identification
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).
Cited literature [32 references]
https://hal-supelec.archives-ouvertes.fr/hal-00609529
Contributor : Yanfu Li <>
Submitted on : Friday, July 27, 2012 - 4:53:10 PM
Last modification on : Monday, December 14, 2020 - 12:28:37 PM
Long-term archiving on: : Sunday, October 28, 2012 - 2:35:22 AM
Contributor : Yanfu Li <>
Submitted on : Friday, July 27, 2012 - 4:53:10 PM
Last modification on : Monday, December 14, 2020 - 12:28:37 PM
Long-term archiving on: : Sunday, October 28, 2012 - 2:35:22 AM
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ANNO_2011_9.pdf
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