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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 (772.8Kb - 13/04/2022)
OrcIDhttps://orcid.org/0000-0003-4232-4161

Contatti
Orario di ricevimento
DipartimentoPianoUfficioGiornoOrarioTelefonoFaxNote
energia----LunedìDalle 15:00
Alle 17:00
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E-mailpiero.baraldi@polimi.it
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 2024
Nessun prodotto attualmente registrato nell'anno 2024


Elenco delle pubblicazioni e dei prodotti della ricerca per l'anno 2023 (Mostra tutto | Nascondi tutto)
Tipologia Titolo Pubblicazione/Prodotto
Contributo in Atti di convegno
A Method based on Natural Language Processing for Periodically Estimating Variations of Performance of Safety Barriers in Hydrocarbon Production Assets (Mostra >>)
Exploiting Explanations to Detect Misclassifications of Deep Learning Models in Power Grid Visual Inspection (Mostra >>)
Optimization Method for an Improved Training of Physics Informed Neural Networks (Mostra >>)
Prediction of the Number of Defectives in a Production Batch of Semiconductor Devices (Mostra >>)
Articoli su riviste
Deep Multiadversarial Conditional Domain Adaptation Networks for Fault Diagnostics of Industrial Equipment (Mostra >>)
Guest Editorial: Special Issue of ESREL2020 PSAM15 (Mostra >>)
Maintenance optimization in industry 4.0 (Mostra >>)
Optimal operation and maintenance of energy storage systems in grid-connected microgrids by deep reinforcement learning (Mostra >>)
The Aramis Data Challenge to prognostics and health management methods for application in evolving environments (Mostra >>)


Elenco delle pubblicazioni e dei prodotti della ricerca per l'anno 2022 (Mostra tutto | Nascondi tutto)
Tipologia Titolo Pubblicazione/Prodotto
Contributi su volumi (Capitolo o Saggio)
Optimal Management of the Flow of Parts for Gas Turbines Maintenance by Reinforcement Learning and Artificial Neural Networks (Mostra >>)
Contributo in Atti di convegno
A Taxonomy for Modelling Reports of Process Safety Events in the Oil and Gas Industry (Mostra >>)
An Unsupervised Method for Anomaly Detection in Multi-Stage Production Systems Based on LSTM Autoencoders (Mostra >>)
Estimation of the Case Temperature of Insulated Gate Bipolar Temperatures in Induction Cooktops by Deep Neural Network (Mostra >>)
Monitoring Degradation of Insulated Gate Bipolar Transistors in Induction Cooktops by Artificial Neural Networks (Mostra >>)
Prediction of the Remaining Useful Life of MOSFETs Used in Automotive Inverters by an Ensemble of Neural Networks (Mostra >>)
Wrapper Selection of Features for Fault Diagnostics of Truss Structures (Mostra >>)
Articoli su riviste
A Niching Augmented Evolutionary Algorithm for the Identification of Functional Dependencies in Complex Technical Infrastructures From Alarm Data (Mostra >>)
A Novel Metric to Evaluate the Association Rules for Identification of Functional Dependencies in Complex Technical Infrastructures (Mostra >>)
A dynamic event tree for a blowout accident in an oil deep-water well equipped with a managed pressure drilling condition monitoring and operation system (Mostra >>)
A framework based on Natural Language Processing and Machine Learning for the classification of the severity of road accidents from reports (Mostra >>)
A method for fault detection in multi-component systems based on sparse autoencoder-based deep neural networks (Mostra >>)
A novelty-based multi-objective evolutionary algorithm for identifying functional dependencies in complex technical infrastructures from alarm data (Mostra >>)
A two-stage estimation method based on Conceptors-aided unsupervised clustering and convolutional neural network classification for the estimation of the degradation level of industrial equipment (Mostra >>)
Generative Adversarial Networks With AdaBoost Ensemble Learning for Anomaly Detection in High-Speed Train Automatic Doors (Mostra >>)
Optimization of the Operation and Maintenance of renewable energy systems by Deep Reinforcement Learning (Mostra >>)


Elenco delle pubblicazioni e dei prodotti della ricerca per l'anno 2021 (Mostra tutto | Nascondi tutto)
Tipologia Titolo Pubblicazione/Prodotto
Contributo in Atti di convegno
A Method based on Gaussian Process Regression for Modelling Burn-in of Semiconductor Devices (Mostra >>)
A Natural Language Processing Method for the Identification of the Factors Influencing Road Accident Severity (Mostra >>)
Damage Detection in Truss Structures Supporting Pipelines and Auxiliary Equipment in Power Plants (Mostra >>)
Natural Language Processing and Bayesian Networks for the Analysis of Process Safety Events (Mostra >>)
Articoli su riviste
A machine learning-based methodology for multi-parametric solution of chemical processes operation optimization under uncertainty (Mostra >>)
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 >>)
Deep reinforcement learning based on proximal policy optimization for the maintenance of a wind farm with multiple crews (Mostra >>)
Identification of critical components in the complex technical infrastructure of the large hadron collider using relief feature ranking and support vector machines (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 >>)
manifesti v. 3.5.17 / 3.5.17
Area Servizi ICT
19/05/2024