A METHOD FOR ESTIMATING THE CONFIDENCE IN THE IDENTIFICATION OF NUCLEAR TRANSIENTS BY A BAGGED ENSEMBLE OF FCM CLASSIFIERS

Piero Baraldi (1) , Roozbeh Razavi-Far (1) , Enrico Zio (1, 2, 3)

1 Dipartimento di Energia [Milano]
2 SSEC - Chaire Sciences des Systèmes et Défis Energétiques EDF/ECP/Supélec
3 LGI - Laboratoire Génie Industriel - EA 2606

The performance of diagnostic systems based on empirical models may vary in different zones of the training space. It is, thus, important to a-priori verify whether the model is working in a zone where the performance is expected to be satisfactory. In this respect, the objective of this work is to estimate the degree of confidence in the identification of nuclear transients by a diagnostic system based on a bagged ensemble of Supervised Fuzzy C-Means (FCM) classifiers. The method has been applied for classifying simulated transients in the feedwater system of a nuclear Boiling Water Reactor (BWR). The obtained results indicate that the bagging ensemble permits to achieve satisfactory performance, with a reliable estimation of the degree of confidence in the classification.

Domaines: Autre

Piero Baraldi, Roozbeh Razavi-Far, Enrico Zio. A METHOD FOR ESTIMATING THE CONFIDENCE IN THE IDENTIFICATION OF NUCLEAR TRANSIENTS BY A BAGGED ENSEMBLE OF FCM CLASSIFIERS. Seventh American Nuclear Society International Topical Meeting on Nuclear Plant Instrumentation, Control and Human-Machine Interface Technologies NPIC&HMIT, 2010, pp.283 - 293. ⟨hal-00721035⟩