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Journal articles
Classifier-Ensemble Incremental-Learning Procedure for Nuclear Transient Identification at Different Operational Conditions
Abstract : An important requirement for the practical implementation of empirical diagnostic systems is the capability of classifying transients in all plant operational conditions. The present paper proposes an approach based on an ensemble of classifiers for incrementally learning transients under different operational conditions. New classifiers are added to the ensemble where transients occurring in new operational conditions are not satisfactorily classified. The construction of the ensemble is made by bagging; the base classifier is a supervised Fuzzy C Means (FCM) classifier whose outcomes are combined by majority voting. The incremental learning procedure is applied to the identification of simulated transients in the feedwater system of a Boiling Water Reactor (BWR) under different reactor power levels.
Cited literature [25 references]
https://hal-supelec.archives-ouvertes.fr/hal-00609522
Contributor : Yanfu Li <>
Submitted on : Friday, July 27, 2012 - 4:57:25 PM
Last modification on : Saturday, May 8, 2021 - 3:26:50 AM
Long-term archiving on: : Sunday, October 28, 2012 - 2:35:15 AM
Contributor : Yanfu Li <>
Submitted on : Friday, July 27, 2012 - 4:57:25 PM
Last modification on : Saturday, May 8, 2021 - 3:26:50 AM
Long-term archiving on: : Sunday, October 28, 2012 - 2:35:15 AM
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ANNO_2011_8.pdf
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