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Francesco Di Maio
Francesco Di Maio
Verified email at polimi.it
Title
Cited by
Cited by
Year
A data-driven fuzzy approach for predicting the remaining useful life in dynamic failure scenarios of a nuclear system
E Zio, F Di Maio
Reliability Engineering & System Safety 95 (1), 49-57, 2010
3912010
Combining relevance vector machines and exponential regression for bearing residual life estimation
F Di Maio, KL Tsui, E Zio
Mechanical systems and signal processing 31, 405-427, 2012
1672012
Hierarchical k-nearest neighbours classification and binary differential evolution for fault diagnostics of automotive bearings operating under variable conditions
P Baraldi, F Cannarile, F Di Maio, E Zio
Engineering Applications of Artificial Intelligence 56, 1-13, 2016
1402016
A particle filtering and kernel smoothing-based approach for new design component prognostics
Y Hu, P Baraldi, F Di Maio, E Zio
Reliability Engineering & System Safety 134, 19-31, 2015
1312015
Fault detection in nuclear power plants components by a combination of statistical methods
F Di Maio, P Baraldi, E Zio, R Seraoui
IEEE Transactions on Reliability 62 (4), 833-845, 2013
1252013
Efficient generation of energetic ions in multi-ion plasmas by radio-frequency heating
YO Kazakov, J Ongena, JC Wright, SJ Wukitch, E Lerche, MJ Mantsinen, ...
Nature Physics 13 (10), 973-978, 2017
1162017
Fatigue crack growth estimation by relevance vector machine
E Zio, F Di Maio
Expert Systems with Applications 39 (12), 10681-10692, 2012
1092012
A data-driven approach for predicting failure scenarios in nuclear systems
E Zio, F Di Maio, M Stasi
Annals of Nuclear Energy 37 (4), 482-491, 2010
852010
Remaining useful life estimation in heterogeneous fleets working under variable operating conditions
S Al-Dahidi, F Di Maio, P Baraldi, E Zio
Reliability Engineering & System Safety 156, 109-124, 2016
742016
Online performance assessment method for a model-based prognostic approach
Y Hu, P Baraldi, F Di Maio, E Zio
IEEE Transactions on reliability 65 (2), 718-735, 2015
712015
Processing dynamic scenarios from a reliability analysis of a nuclear power plant digital instrumentation and control system
E Zio, F Di Maio
Annals of Nuclear Energy 36 (9), 1386-1399, 2009
692009
Safety margins confidence estimation for a passive residual heat removal system
E Zio, F Di Maio, J Tong
Reliability Engineering & System Safety 95 (8), 828-836, 2010
622010
Comparison of data-driven reconstruction methods for fault detection
P Baraldi, F Di Maio, D Genini, E Zio
IEEE Transactions on Reliability 64 (3), 852-860, 2015
612015
Robust signal reconstruction for condition monitoring of industrial components via a modified Auto Associative Kernel Regression method
P Baraldi, F Di Maio, P Turati, E Zio
Mechanical Systems and Signal Processing 60, 29-44, 2015
602015
Quantifying uncertainties in the estimation of safety parameters by using bootstrapped artificial neural networks
P Secchi, E Zio, F Di Maio
Annals of Nuclear Energy 35 (12), 2338-2350, 2008
602008
Ensemble-approaches for clustering health status of oil sand pumps
F Di Maio, J Hu, P Tse, M Pecht, K Tsui, E Zio
Expert Systems with applications 39 (5), 4847-4859, 2012
592012
Unsupervised clustering for fault diagnosis in nuclear power plant components
P Baraldi, F Di Maio, E Zio
International Journal of Computational Intelligence Systems 6 (4), 764-777, 2013
542013
A Monte Carlo-based exploration framework for identifying components vulnerable to cyber threats in nuclear power plants
W Wang, A Cammi, F Di Maio, S Lorenzi, E Zio
Reliability Engineering & System Safety 175, 24-37, 2018
492018
Clustering for unsupervised fault diagnosis in nuclear turbine shut-down transients
P Baraldi, F Di Maio, M Rigamonti, E Zio, R Seraoui
Mechanical Systems and Signal Processing 58, 160-178, 2015
492015
Reconstruction of missing data in multidimensional time series by fuzzy similarity
P Baraldi, F Di Maio, D Genini, E Zio
Applied Soft Computing 26, 1-9, 2015
482015
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Articles 1–20