D. Roverso, M. Hoffmann, E. Zio, P. Baraldi, and G. Gola, Solutions for plant-wide on-line calibration monitoring, Proc. ESREL 2007, pp.827-832, 2007.

E. Zio, P. Baraldi, G. Gola, D. Roverso, and M. Hoffmann, Genetic Algoritms for Grouping of Signals for System Monitoring and Diagnostics, Proc. ESREL 2007, pp.833-840, 2007.

P. Baraldi, E. Zio, G. Gola, D. Roverso, and M. Hoffmann, Genetic algorithms for signal grouping in sensor validation: a comparison of the filter and wrapper approaches, Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, vol.222, issue.2, 2007.
DOI : 10.1243/1748006XJRR137

]. M. Perrone and L. N. Cooper, When networks disagree: Ensemble methods for hybrid neural networks, National Science Fundation, vol.7, 1992.
DOI : 10.1142/9789812795885_0025

A. Krogh and J. Vedelsby, Neural network ensembles, cross-validation and active learning

S. Touretzky, T. K. Loen8-]-a, and . Sharkey, Advances in newel information processing systems On combining artificial neural nets, Connection Science, vol.79, issue.83, pp.231-238, 1995.

J. H. Holland, Adaptation in natural and artificial systems: an introductory analysis with application to biology, Control and Artificial Intelligence, 1975.

D. E. Goldberg, Genetic algorithms in search, optimization, and machine learning, 1989.

L. Chambers, Practical handbook of genetic algorithms: applications Vol. I; new frontiers, 1995.

Y. Sawaragy, H. Nakayama, and T. Tanino, Theory of multiobjective optimization, 1985.

M. L. Raymer, W. F. Punch, E. D. Goodman, L. A. Khun, and A. K. Jain, Dimensionality reduction using genetic algorithms, IEEE Transactions on Evolutionary Computation, vol.4, issue.2, 2000.
DOI : 10.1109/4235.850656

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

H. Bozdogan and H. Bozdogan, Statistical Data Mining with Informational Complexity and Genetic Algorithm Statistical Data Mining and knowledge discovery, 2003.

I. T. Jolliffe, Principal Component Analysis, 2002.
DOI : 10.1007/978-1-4757-1904-8

K. I. Diamantaras and S. Y. Kung, Principal component neural networks: theory and applications, 1996.

B. Scholkopf, A. Smola, and K. R. Muller, Kernel principal component analysis, Advances in Kernel Methods- Support Vector Learning, 1999.
DOI : 10.1007/BFb0020217

B. Moore, Principal component analysis in linear systems: Controllability, observability, and model reduction, IEEE Transactions on Automatic Control, vol.26, issue.1, 1981.
DOI : 10.1109/TAC.1981.1102568

P. Baldi and K. Hornik, Neural networks and principal component analysis: Learning from examples without local minima, Neural Networks, vol.2, issue.1, pp.53-58, 1989.
DOI : 10.1016/0893-6080(89)90014-2

E. Zio, P. Baraldi, and N. Pedroni, Selecting features for nuclear transients classification by means of genetic algorithms, IEEE Transactions on Nuclear Science, vol.53, issue.3, 2006.
DOI : 10.1109/TNS.2006.873868

G. Gola, E. Zio, P. Baraldi, D. Roverso, and M. Hoffmann, Signal Grouping for Sensor Validation: a Multi- Objective Genetic Algorithm Approach, 2007.

I. Lawrence and L. Kuei, A Concordance Correlation Coefficient to Evaluate Reproducibility, Biometrics, vol.45, issue.1, pp.255-268, 1989.

R. J. Hunt, Percent Agreement, Pearson's Correlation, and Kappa as Measures of Inter-examiner Reliability, Journal of Dental Research, vol.65, issue.2, pp.128-130, 1986.
DOI : 10.1177/00220345860650020701

A. Kirschner and M. Hoffmann, PEANO NNPLS: Advancements in 2002-03, 2004.

R. W. Hamming, Error Detecting and Error Correcting Codes, Bell System Technical Journal, vol.29, issue.2, pp.147-160, 1950.
DOI : 10.1002/j.1538-7305.1950.tb00463.x

URL : http://campus.unibo.it/10913/1/hamming1950.pdf

G. D. Forney-jr, M. Codex, and M. A. Mansfield, On the Hamming distance properties of group codes, IEEE Transactions on Information Theory, vol.38, issue.6, pp.1797-1801, 1992.
DOI : 10.1109/18.165454

E. Zio, P. Baraldi, and G. Gola, Feature-based classifier ensembles for diagnosing multiple faults in rotating machinery, Applied Soft Computing, vol.8, issue.4, 2007.
DOI : 10.1016/j.asoc.2007.10.005