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Le informazioni sulla didattica, sulla ricerca e sui compiti istituzionali riportate in questa pagina sono certificate dall'Ateneo; ulteriori informazioni, redatte a cura del docente, sono disponibili sulla pagina web personale e nel curriculum vitae indicati nella scheda.
Informazioni sul docente
DocenteBaraldi Piero
QualificaProfessore ordinario a tempo pieno
Dipartimento d'afferenzaDipartimento di Energia
Settore Scientifico DisciplinareING-IND/19 - Impianti Nucleari
Curriculum VitaeScarica il CV (121.35Kb - 22/01/2018)

Orario di ricevimento
energia----LunedìDalle 15:00
Alle 17:00
Pagina web redatta a cura del docentewww.lasar.polimi.it

Fonte dati: RE.PUBLIC@POLIMI - Research Publications at Politecnico di Milano

Elenco delle pubblicazioni e dei prodotti della ricerca per l'anno 2021 (Mostra tutto | Nascondi tutto)
Tipologia Titolo Pubblicazione/Prodotto
Articoli su riviste
A method for fault diagnosis in evolving environment using unlabeled data (Mostra >>)
A multi-branch deep neural network model for failure prognostics based on multimodal data (Mostra >>)
A novel association rule mining method for the identification of rare functional dependencies in Complex Technical Infrastructures from alarm data (Mostra >>)
A semi-supervised method for the characterization of degradation of nuclear power plants steam generators (Mostra >>)
Association rules extraction for the identification of functional dependencies in complex technical infrastructures (Mostra >>)
Bootstrapped ensemble of artificial neural networks technique for quantifying uncertainty in prediction of wind energy production (Mostra >>)

Elenco delle pubblicazioni e dei prodotti della ricerca per l'anno 2020 (Mostra tutto | Nascondi tutto)
Tipologia Titolo Pubblicazione/Prodotto
Contributo in Atti di convegno
A coevolutionary optimization approach with deep sparse autoencoder for the extraction of equipment degradation indicators (Mostra >>)
A method for inferring casual dependencies among abnormal behaviours of components in complex technical infrastructures (Mostra >>)
A methodology for the identification of the critical components of the electrical distribution network of cern’s large hadron collider (Mostra >>)
A novel degradation state indicator for steam generators of nuclear power plants (Mostra >>)
Agent-based modeling and reinforcement learning for optimizing energy systems operation and maintenance: the pathmind solution (Mostra >>)
An ensemble of echo state networks for predicting the energy production of wind plants (Mostra >>)
An unsupervised method for the reconstruction of maintenance intervention times (Mostra >>)
Data-driven extraction of association rules of dependent abnormal behaviour groups (Mostra >>)
Data-driven identification of critical components in complex technical infrastructures using Bayesian additive regression trees (Mostra >>)
Deep reinforcement learning for optimizing operation and maintenance of energy systems equipped with phm capabilities (Mostra >>)
Fault detection based on optimal transport theory (Mostra >>)
Fault diagnostics by conceptors-aided clustering (Mostra >>)
Fault prognostics in presence of event-based measurements (Mostra >>)
Multi-objective evolutionary algorithm for the identification of rare functional dependencies in complex technical infrastructures (Mostra >>)
Text mining for the automatic classification of road accident reports (Mostra >>)
The aramis data challenge: Prognostics and health management in evolving environments (Mostra >>)
Articoli su riviste
A Feature Selection-based Approach for the Identification of Critical Components in Complex Technical Infrastructures: Application to the CERN Large Hadron Collider (Mostra >>)
A Novel Concept Drift Detection Method for Incremental Learning in Nonstationary Environments (Mostra >>)
A data-driven framework for identifying important components in complex systems (Mostra >>)
A novel method for maintenance record clustering and its application to a case study of maintenance optimization (Mostra >>)
Challenges to IoT-Enabled Predictive Maintenance for Industry 4.0 (Mostra >>)
Dynamic Surrogate Modeling for Multistep-ahead Prediction of Multivariate Nonlinear Chemical Processes (Mostra >>)
Ensemble empirical mode decomposition and long short-term memory neural network for multi-step predictions of time series signals in nuclear power plants (Mostra >>)
Fault prognostics by an ensemble of Echo State Networks in presence of event based measurements (Mostra >>)
Industrial equipment reliability estimation: A Bayesian Weibull regression model with covariate selection (Mostra >>)
Partially observable Markov decision processes for optimal operations of gas transmission networks (Mostra >>)

Elenco delle pubblicazioni e dei prodotti della ricerca per l'anno 2019 (Mostra tutto | Nascondi tutto)
Tipologia Titolo Pubblicazione/Prodotto
Scheda Bibliografica
An evidential similarity-based regression method for the prediction of equipment remaining useful life in presence of incomplete degradation trajectories (Mostra >>)
Contributo in Atti di convegno
Automatic Extraction of a Health Indicator from Vibrational Data by Sparse Autoencoders (Mostra >>)
Articoli su riviste
An ensemble of models for integrating dependent sources of information for the prognosis of the remaining useful life of Proton Exchange Membrane Fuel Cells (Mostra >>)
Elastic net multinomial logistic regression for fault diagnostics of on-board aeronautical systems (Mostra >>)

Elenco delle pubblicazioni e dei prodotti della ricerca per l'anno 2018 (Mostra tutto | Nascondi tutto)
Tipologia Titolo Pubblicazione/Prodotto
Contributo in Atti di convegno
A heterogeneous ensemble approach for the prediction of the remaining useful life of packaging industry machinery (Mostra >>)
A smart framework for the availability and reliability assessment and management of accelerators technical facilities (Mostra >>)
Dealing with uncertainty in modelling of wastewater disinfection by peracetic acid (Mostra >>)
Articoli su riviste
A Markov decision process framework for optimal operation of monitored multi-state systems (Mostra >>)
A Novel Method for Sensor Data Validation based on the analysis of Wavelet Transform Scalograms (Mostra >>)
A framework for reconciliating data clusters from a fleet of nuclear power plants turbines for fault diagnosis (Mostra >>)
An Ensemble of Component-Based and Population-Based Self-Organizing Maps for the Identification of the Degradation State of Insulated-Gate Bipolar Transistors (Mostra >>)
Differential evolution-based multi-objective optimization for the definition of a health indicator for fault diagnostics and prognostics (Mostra >>)
Homogeneous Continuous-Time, Finite-State Hidden Semi-Markov Modeling for Enhancing Empirical Classification System Diagnostics of Industrial Components (Mostra >>)
Hybrid Probabilistic-Possibilistic Treatment of Uncertainty in Building Energy Models: A Case Study of Sizing Peak Cooling Loads (Mostra >>)

Elenco delle pubblicazioni e dei prodotti della ricerca per l'anno 2017 (Mostra tutto | Nascondi tutto)
Tipologia Titolo Pubblicazione/Prodotto
Contributo in Atti di convegno
A Dynamic Weighting Ensemble Approach for Wind Energy Production Prediction (Mostra >>)
A Hybrid Monte Carlo and Possibilistic Approach to Estimate Non-Suppression Probability in Fire Probabilistic Safety Analysis (Mostra >>)
A switching ensemble approach for remaining useful life estimation of electrolytic capacitors (Mostra >>)
An unsupervised clustering method for assessing the degradation state of cutting tools used in the packaging industry (Mostra >>)
Resistance-based probabilistic design by order statistics for an oil and gas deep-water well casing string affected by wear during kick load (Mostra >>)
Articoli su riviste
A Systematic Semi-Supervised Self-adaptable Fault Diagnostics approach in an evolving environment (Mostra >>)
A locally adaptive ensemble approach for data-driven prognostics of heterogeneous fleets (Mostra >>)
Development of a Bayesian multi-state degradation model for up-to-date reliability estimations of working industrial components (Mostra >>)
Ensemble of optimized echo state networks for remaining useful life prediction (Mostra >>)
Prediction of industrial equipment Remaining Useful Life by fuzzy similarity and belief function theory (Mostra >>)
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