J. Reifman, ?Survey of artificial intelligence methods for detection and identification of component faults in nuclear power plants, Nucl. Technol, vol.119, pp.76-97, 1997.

K. E. Holbert and B. R. Upadhyaya, ?An integrated signal validation system for nuclear power plants, Nuclear Technology, vol.92, pp.411-427, 1990.

B. R. Upadhyaya and E. , Eryurek, ?Application of neural networks for sensor validation and plant monitoring, Nuclear Technology, vol.97, pp.170-176, 1992.

P. F. Fantoni and A. Mazzola, A pattern recognition-artificial neural networks based model for signal validation in nuclear power plants, Annals of Nuclear Energy, vol.23, issue.13, pp.1069-1076, 1996.
DOI : 10.1016/0306-4549(96)84661-5

J. W. Hines, D. J. Wrest, and R. E. , Uhrig, ?Signal validation using an adaptive neural fuzzy inference system, Nuclear Technology, vol.119, pp.181-193, 1997.

A. S. Erbay and B. R. Upadhyaya, ?A personal computer-based on-line validation system for nuclear power plants, Nuclear Technology, vol.119, pp.63-75, 1997.

J. W. Hines and R. E. , Uhrig, ?Use of autoassociative neural networks for signal validation, Journal of Intelligent and Robotic Systems, vol.21, issue.2, pp.143-154, 1998.
DOI : 10.1023/A:1007981322574

B. Rasmussen, J. W. Hines, and R. E. , Uhrig, ?Novel Approach to Process Modeling for Instrument Surveillance and Calibration Verification, Proceedings of the Third American Nuclear Society International Topical Meeting on Nuclear Plant Instrumentation and Control and Human-Machine Interface Technologies, 2000.

E. Zio, M. Broggi, and N. Pedroni, ?Nuclear reactor dynamics on-line estimation by locally recurrent neural networks,? Progress in Nuclear Energy, pp.573-581, 2009.

R. Penha and J. W. , Hines, ?Using principal component analysis modeling to monitor temperature sensors in a nuclear research reactor, Proceedings of the 2001 Maintenance and Reliability Conference, 2001.

J. Ding, J. W. Hines, and R. Rasmussen, ?Independent component analysis for redundant sensor validation, Proceedings of the 2003 Maintenance and Reliability Conference, 2003.

P. Baraldi, E. Zio, G. Gola, D. Roverso, and M. Hoffmann, Signal reconstruction by a GA-optimized ensemble of PCA models, Nuclear Engineering and Design, vol.241, issue.1, pp.301-309, 2011.
DOI : 10.1016/j.nucengdes.2010.10.012

URL : https://hal.archives-ouvertes.fr/hal-00609542

R. M. Singer, K. C. Gross, and R. W. , King, ?Application of pattern recognition techniques to online fault detection, Proceedings of the Second Probability Safety Assessment Meeting (PSAM-II), 1994.

R. M. Singer, K. C. Gross, R. W. King, and S. Wegerich, ?A pattern recognition based, fault-tolerant monitoring and diagnostic techniques symposium on nuclear reactor surveillance and diagnostics,? SMORN VII, pp.13-14, 1995.

N. Zavaljevski and K. C. , Gross, ?Support vector machines for nuclear reactor state estimation, Proceedings of the ANS Topical Meeting on Advances in Reactor Physics and Mathematics and Computation into the Next Millennium, 2000.

C. M. Rocco and E. Zio, A support vector machine integrated system for the classification of operation anomalies in nuclear components and systems, Reliability Engineering & System Safety, vol.92, issue.5, pp.593-600, 2007.
DOI : 10.1016/j.ress.2006.02.003

J. W. Hines and D. R. Garvey, Development and Application of Fault Detectability Performance Metrics for Instrument Calibration Verification and Anomaly Detection, Journal of Pattern Recognition Research, vol.1, issue.1, pp.2-15, 2006.
DOI : 10.13176/11.5

R. Chevalier, D. Provost, and R. , Seraoui, ?Assessment of statistical and classification model for monitoring EDF's assets,? Sixth American Nuclear Society International Topical Meeting on Nuclear Plant Instrumentation, Control and Human-Machine Interface Technologies, 2009.

P. Baraldi, R. Canesi, E. Zio, R. Seraoui, and R. Chevalier, ?Signal Grouping for Condition Monitoring of Nuclear Power Plants Components,? Seventh American Nuclear Society International Topical Meeting on Nuclear Plant Instrumentation, Control and Human-Machine Interface Technologies, 2010.

P. Baraldi, F. Di-maio, L. Pappaglione, E. Zio, and R. Seraoui, Condition monitoring of electrical power plant components during operational transients, Proceedings of the Institution of Mechanical Engineers, pp.568-583, 2012.
DOI : 10.1177/1748006X12463502

URL : https://hal.archives-ouvertes.fr/hal-00765275

C. Yu and B. Su, Eliminating false alarms caused by fault propagation in signal validation by sub-grouping, Progress in Nuclear Energy, pp.371-379, 2006.
DOI : 10.1016/j.pnucene.2005.09.013

A. Krogh and J. Vedelsby, ?Neural network ensembles, cross-validation and active learning, Advances in Newel Information Processing Systems, pp.231-238, 1995.

A. J. Sharkey, ?On combining artificial neural nets,? Connection Science, pp.299-314, 1996.

P. Baraldi, E. Zio, G. Gola, D. Roverso, and M. Hoffmann, Robust nuclear signal reconstruction by a novel ensemble model aggregation procedure, International Journal of Nuclear Knowledge Management, vol.4, issue.1, pp.34-41, 2010.
DOI : 10.1504/IJNKM.2010.031153

URL : https://hal.archives-ouvertes.fr/hal-00609150

P. Baraldi, G. Gola, E. Zio, D. Roverso, and M. Hoffmann, ?A randomized model ensemble approach for reconstructing signals from faulty sensors,? Expert System With Application, pp.9211-9224, 2011.

H. Adeli and S. Kumar, Distributed Genetic Algorithm for Structural Optimization, Journal of Aerospace Engineering, vol.8, issue.3, pp.156-163, 1995.
DOI : 10.1061/(ASCE)0893-1321(1995)8:3(156)

A. Tucker, S. Swift, and X. Liu, Variable grouping in multivariate time series via correlation, IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics), vol.31, issue.2, 2001.
DOI : 10.1109/3477.915346

P. Baraldi, E. Zio, G. Gola, D. Roverso, and M. Hoffmann, Two novel procedures for aggregating randomized model ensemble outcomes for robust signal reconstruction in nuclear power plants monitoring systems, Annals of Nuclear Energy, vol.38, issue.2-3, pp.38-212, 2011.
DOI : 10.1016/j.anucene.2010.11.007

URL : https://hal.archives-ouvertes.fr/hal-00609545

P. Baraldi, R. Canesi, E. Zio, R. Seraoui, and R. Chevalier, ?Genetic algorithm-based wrapper approach for grouping condition monitoring signal of nuclear power plant components, pp.221-234, 2011.

P. Baraldi, E. Zio, F. Di-maio, L. Pappaglione, R. Chevalier et al., Differential evolution for optimal grouping of condition monitoring signals of nuclear components, Proceedings of the European Safety and Reliability Conference 2011, pp.410-418, 2011.
DOI : 10.1201/b11433-59

URL : https://hal.archives-ouvertes.fr/hal-00658087

R. Kohavi and G. John, Wrappers for feature subset selection, Artificial Intelligence, vol.97, issue.1-2, pp.273-324, 1997.
DOI : 10.1016/S0004-3702(97)00043-X

K. C. Gross and W. Lu, ?Early detection of signal and process anomalies in enterprise computing systems, International Conference on Machine Learning and Applications -ICMLA, pp.204-210, 2002.

S. Chen and M. , Using cross-validation for model parameter selection of sequential probability ratio test, Expert Systems with Applications, vol.39, issue.9, pp.8467-8473, 2012.
DOI : 10.1016/j.eswa.2012.01.172

H. Sohn, D. W. Allen, K. Worden, and C. R. Farrar, ?Statistical damage classification using sequential probability ratio tests,? Structural Health Monitoring, pp.57-74, 2003.
DOI : 10.1177/147592103031113

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=

E. Samuel, Randomized Sequential Tests. A Comparison between Curtailed Single-Sampling Plans and Sequential Probability Ratio Tests, Journal of the American Statistical Association, vol.65, issue.329, pp.431-437, 1970.
DOI : 10.1214/aoms/1177703886

K. E. Humenik and K. C. , Gross, ?Sequential probability ratio tests for nuclear plant component surveillance, Nuclear Technology, vol.93, 1991.

S. Tantaratana, A. W. Lam, and P. J. Vincent, Noncoherent sequential acquisition of PN sequences for DS/SS communications with/without channel fading, IEEE Transactions on Communications, vol.43, issue.2/3/4, pp.1738-1745, 1995.
DOI : 10.1109/26.380224

D. C. Montgomery, E. A. Peck, and G. G. , Vining, ?Introduction to Linear Regression Analysis, 2001.