期刊
RELIABILITY ENGINEERING & SYSTEM SAFETY
卷 96, 期 4, 页码 480-488出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.ress.2010.11.005
关键词
Classification; Fuzzy C Means (FCM) clustering; Bagging; Ensemble; Incremental learning; BWR nuclear power plant; Transient identification
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. (C) 2010 Elsevier Ltd. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据