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2020 – today
- 2024
[j15]Álvaro García
, Aníbal Bregón, Miguel A. Martínez-Prieto:
Digital Twin Learning Ecosystem: A cyber-physical framework to integrate human-machine knowledge in traditional manufacturing. Internet Things 25: 101094 (2024)- [j14]Jorge Silvestre, Miguel A. Martínez-Prieto, Aníbal Bregón, Pedro C. Álvarez-Esteban:
A deep learning-based approach for predicting in-flight estimated time of arrival. J. Supercomput. 80(12): 17212-17246 (2024) - [c14]Jorge Silvestre, Paula Mielgo, Aníbal Bregón, Miguel A. Martínez-Prieto, Pedro C. Álvarez-Esteban:
Towards aircraft trajectory prediction using LSTM networks. SAC 2024: 1059-1060 - 2023
- [j13]Diego García-Álvarez, Aníbal Bregón, Belarmino Pulido, Carlos J. Alonso-González:
Integrating PCA and structural model decomposition to improve fault monitoring and diagnosis with varying operation points. Eng. Appl. Artif. Intell. 122: 106145 (2023) - 2022
- [j12]Álvaro García, Aníbal Bregón, Miguel A. Martínez-Prieto:
A non-intrusive Industry 4.0 retrofitting approach for collaborative maintenance in traditional manufacturing. Comput. Ind. Eng. 164: 107896 (2022) - [j11]Álvaro García, Aníbal Bregón, Miguel A. Martínez-Prieto:
Towards a connected Digital Twin Learning Ecosystem in manufacturing: Enablers and challenges. Comput. Ind. Eng. 171: 108463 (2022)
2010 – 2019
- 2019
- [j10]Carlos J. Alonso-González, Belarmino Pulido, Mario Cartón, Aníbal Bregón:
A Big Data Architecture for Fault Prognostics of Electronic Devices: Application to Power MOSFETs. IEEE Access 7: 102160-102173 (2019) - [j9]Belarmino Pulido, Jesús M. Zamarreño, Alejandro Merino Gómez, Aníbal Bregón:
State space neural networks and model-decomposition methods for fault diagnosis of complex industrial systems. Eng. Appl. Artif. Intell. 79: 67-86 (2019) - 2017
- [c13]Iván García, Miguel A. Martínez-Prieto, Aníbal Bregón, Pedro C. Álvarez, Fernando Díaz:
Towards a Scalable Architecture for Flight Data Management. DATA 2017: 263-268 - [c12]Carlos J. Alonso-González, Aníbal Bregón, Belarmino Pulido, Matías A. Nacusse, Sergio J. Junco:
Autonomous vehicle traction subsystem modeling and diagnosis using BG-PCs. DX 2017: 94-109 - 2016
- [j8]Matthew J. Daigle, Aníbal Bregón, Xenofon D. Koutsoukos, Gautam Biswas, Belarmino Pulido:
A qualitative event-based approach to multiple fault diagnosis in continuous systems using structural model decomposition. Eng. Appl. Artif. Intell. 53: 190-206 (2016) - [j7]Belarmino Pulido, Aníbal Bregón, Carlos J. Alonso-González, Alberto Hernández, David Rubio, Luis Miguel Villarroel:
DxPCs: a toolbox for model-based diagnosis of dynamic systems using possible conflicts. Prog. Artif. Intell. 5(2): 111-120 (2016) - 2015
- [c11]Belarmino Pulido, Carlos Alonso González, Aníbal Bregón, Alberto Hernández:
Characterizing and Computing HBG-PCs for Hybrid Systems Fault Diagnosis. CAEPIA 2015: 116-127 - [c10]Aníbal Bregón, Carlos Alonso González, Belarmino Pulido:
Improving Fault Isolation and Identification for Hybrid Systems with Hybrid Possible Conflicts. DX 2015: 59-66 - [c9]Matthew J. Daigle, Aníbal Bregón, Indranil Roychoudhury:
A Structural Model Decomposition Framework for Hybrid Systems Diagnosis. DX 2015: 201-208 - 2014
- [j6]Aníbal Bregón, Matthew J. Daigle, Indranil Roychoudhury, Gautam Biswas, Xenofon D. Koutsoukos, Belarmino Pulido:
An event-based distributed diagnosis framework using structural model decomposition. Artif. Intell. 210: 1-35 (2014) - [j5]Matthew J. Daigle, Aníbal Bregón, Indranil Roychoudhury:
Distributed Prognostics Based on Structural Model Decomposition. IEEE Trans. Reliab. 63(2): 495-510 (2014) - [j4]Aníbal Bregón, Gautam Biswas, Belarmino Pulido, Carlos Alonso González, Hamed Khorasgani:
A Common Framework for Compilation Techniques Applied to Diagnosis of Linear Dynamic Systems. IEEE Trans. Syst. Man Cybern. Syst. 44(7): 863-876 (2014) - [j3]Aníbal Bregón, Carlos J. Alonso-González, Belarmino Pulido:
Integration of Simulation and State Observers for Online Fault Detection of Nonlinear Continuous Systems. IEEE Trans. Syst. Man Cybern. Syst. 44(12): 1553-1568 (2014) - 2013
- [c8]Noemi Moya Alonso, Aníbal Bregón, Carlos J. Alonso-González, Belarmino Pulido:
A Common Framework for Fault Diagnosis of Parametric and Discrete Faults Using Possible Conflicts. CAEPIA 2013: 239-249 - 2012
- [j2]Aníbal Bregón, Gautam Biswas, Belarmino Pulido:
A Decomposition Method for Nonlinear Parameter Estimation in TRANSCEND. IEEE Trans. Syst. Man Cybern. Part A 42(3): 751-763 (2012) - [j1]Erik Frisk, Aníbal Bregón, Jan Åslund, Mattias Krysander, Belarmino Pulido, Gautam Biswas:
Diagnosability Analysis Considering Causal Interpretations for Differential Constraints. IEEE Trans. Syst. Man Cybern. Part A 42(5): 1216-1229 (2012) - 2011
- [c7]Diego García-Álvarez, Aníbal Bregón, Maria J. Fuente, Belarmino Pulido Junquera:
Improving parameter estimation using minimal analytically redundant subsystems. CDC/ECC 2011: 7788-7793
2000 – 2009
- 2009
- [c6]Belarmino Pulido Junquera, Aníbal Bregón, Carlos Alonso González:
Analyzing the Influence of Differential Constraints in Possible Conflict and ARR Computation. CAEPIA 2009: 11-21 - [c5]Aníbal Bregón, Belarmino Pulido, Gautam Biswas, Xenofon D. Koutsoukos:
Generating Possible Conflicts From Bond Graphs Using Temporal Causal Graphs. ECMS 2009: 675-682 - 2008
- [c4]Belarmino Pulido Junquera, Aníbal Bregón, Carlos Alonso González:
Improving robustness in consistency-based diagnosis using possible conflicts. ECAI 2008: 791-792 - 2007
- [c3]Carlos J. Alonso, Oscar J. Prieto, Juan José Rodríguez, Aníbal Bregón, Belarmino Pulido Junquera:
Stacking Dynamic Time Warping for the Diagnosis of Dynamic Systems. CAEPIA 2007: 11-20 - 2006
- [c2]Oscar J. Prieto, Aníbal Bregón:
A comparison of two machine-learning techniques to focus the diagnosis task. STAIRS 2006: 265-266 - 2005
- [c1]Aníbal Bregón, María Aránzazu Simón Hurtado, Juan José Rodríguez, Carlos J. Alonso, Belarmino Pulido Junquera, Q. Isaac Moro:
Early Fault Classification in Dynamic Systems Using Case-Based Reasoning. CAEPIA 2005: 211-220
Coauthor Index
aka: Belarmino Pulido
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