An ensemble approach to sensor fault detection and signal reconstruction for nuclear system control

Author:

Baraldi Piero,Cammi Antonio,Mangili Francesca,Zio Enrico

Publisher

Elsevier BV

Subject

Nuclear Energy and Engineering

Reference27 articles.

1. Novel methods for the feature subset ensembles approach;Aly;International Journal of Artificial Intelligence and Machine Learning,2006

2. Genetic algorithms for signal grouping in sensor validation: a comparison of the filter and wrapper approaches;Baraldi;Journal of Risk and Reliability (JRR), Proceedings of IMechE,2008

3. Baraldi, P., Zio, E., Gola, G., Roverso, D., Hoffmann, M., 2009. A procedure for the reconstruction of faulty signals by means of an ensemble of regression models based on principal components analysis, NPIC-HMIT 2009 Topical Meeting, April 5–9.

4. Local fusion of an ensemble of models for the reconstruction of faulty signals;Baraldi;IEEE Transactions on Nuclear Science,2010

5. Fast meta-models for local fusion of multiple predictive models;Bonissone;Applied Soft Computing Journal,2008

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