Sfoglia per Relatore
Data, text and image processing by deep learning and extreme learning machine for prognostics and health management
YANG, ZHE
A deep reinforcement learning-based framework for optimal operation and maintenance of complex assets of the energy industry
2021/2022 PINCIROLI, LUCA
Definition of a health indicator for component failure prognostics
2014/2015 BONFANTI, GIANLUCA
development and application of an importance measures for predictive maintenance in oil and gas installations
2016/2017 MOHAMED, AHMED GAMAL HUSSEIN HASSAN
Development of an unsupervised method based on the differential importance measure (DIM) for the condition monitoring of power production plants
2019/2020 FLOREALE, GIOVANNI
Development of prognostics and health management methods for engineering systems operating in evolving environments
HU, YANG
Development of unsupervised and semi-supervised clustering-based methods for degradation assessment of nuclear power plant steam generators
2016/2017 PINCIROLI, LUCA
Ensemble of echo state networks for predicting the energy production of power plants
2017/2018 NIGRO, ELEONORA
Ensemble of neural networks for fault prognostics of industrial equipments
2010/2011 SAUCO, SERGIO
Forecasting by artificial intelligence in the energy industry : feature selection for prediction by artificial neural networks
2017/2018 FRESC, MIRIAM
Homogeneous continuous time discrete state hidden semi-Markov modeling, hierarchical KNN nearest neighbours classification and differential evolution optimization for fault diagnostics and prognostics
2013/2014 CANNARILE, FRANCESCO
Optimal grouping of signals for condition monitoring of nuclear components
2009/2010 CANESI, ROBERTO
Self-organizing maps for condition based maintenance of industrial components
2013/2014 ALESSI, ALLEGRA
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