Daniel Pérez López

@article{garcia_conditioned_2024,

title = {Conditioned fully convolutional denoising autoencoder for multi-target NILM},

author = {Diego García and Daniel Pérez and Panagiotis Papapetrou and Ignacio Díaz and Abel A Cuadrado and José María Enguita and Manuel Domínguez},

url = {https://doi.org/10.1007/s00521-024-10552-0},

doi = {10.1007/s00521-024-10552-0},

issn = {1433-3058},

year  = {2024},

date = {2024-12-05},

urldate = {2024-12-01},

journal = {Neural Computing and Applications},

keywords = {MACHINE LEARNING, SUPERVISIÓN ENERGÉTICA EN EDIFICIOS},

pubstate = {forthcoming},

tppubtype = {article}

}

@article{alonso23,

title = {Gap imputation in related multivariate time series through recurrent neural network-based denoising autoencoder},

author = {Serafín Alonso and Antonio Morán and Daniel Pérez and Miguel A Prada and Juan J Fuertes and Manuel Domínguez},

doi = {10.3233/ICA-230728},

isbn = {1875-8835},

year  = {2024},

date = {2024-01-30},

urldate = {2024-00-00},

journal = {Integrated Computer-Aided Engineering},

volume = {31},

issue = {2},

pages = {157-172},

keywords = {MACHINE LEARNING, SUPERVISIÓN ENERGÉTICA EN EDIFICIOS},

pubstate = {published},

tppubtype = {article}

}

@article{Rodríguez-Ossorio2023,

title = {Echo State Networks for anomaly detection in industrial systems},

author = {José Ramón Rodríguez-Ossorio and Antonio Morán and Serafín Alonso and Daniel Pérez and Ignacio Díaz and Manuel Domínguez},

doi = {10.1016/j.ifacol.2023.10.1836},

issn = {2405-8963},

year  = {2023},

date = {2023-11-22},

urldate = {2023-11-22},

journal = {IFAC-PapersOnLine},

volume = {56},

number = {2},

pages = {1472--1477},

publisher = {Elsevier BV},

keywords = {AUTOMATIZACIÓN CONTROL Y SUPERVISIÓN INDUSTRIAL, MACHINE LEARNING},

pubstate = {published},

tppubtype = {article}

}

@article{Gonzalez2022TwoStep,

title = {Two-step residual-error based approach for anomaly detection in engineering systems using variational autoencoders},

author = {Ana González and Ignacio Díaz and Abel A Cuadrado and Diego García and Daniel Pérez},

doi = {https://doi.org/10.1016/j.compeleceng.2022.108065},

issn = {0045-7906},

year  = {2022},

date = {2022-07-01},

urldate = {2022-01-01},

journal = {Computers and Electrical Engineering},

volume = {101},

pages = {108065},

abstract = {Anomaly detection is a crucial task in the engineering systems field. However, there is usually little or no information about all possible abnormal modes in systems. Hence, a common approach is to build a model of healthy behaviour, based on normal operation data, so that anomaly detection would depend on how well new data fit this model. According to this idea, we propose a residual-error based approach consisting of: a variational autoencoder, used to model the probability density function of the system’s healthy behaviour; and a two-step classification algorithm, which classifies the incoming samples based on their residuals, and reports not only their normal/anomalous nature but also that of their components. We have tested this proposal in three different engineering contexts and we have compared its performance with that of state-of-the-art approaches, demonstrating its capability to successfully detect and characterize anomalies.},

keywords = {MACHINE LEARNING},

pubstate = {published},

tppubtype = {article}

}

@article{domínguez_2022_design,

title = {Design of Platforms for Experimentation in Industrial Cybersecurity},

author = {Manuel Domínguez and Juan J Fuertes and Miguel A Prada and Serafín Alonso and Antonio Morán and Daniel Pérez},

doi = {10.3390/APP12136520},

issn = {2076-3417},

year  = {2022},

date = {2022-06-27},

urldate = {2022-01-01},

journal = {Applied Sciences (Switzerland)},

volume = {12},

number = {13},

publisher = {MDPI},

keywords = {CIBERSEGURIDAD EN INFRAESTRUCTURAS CRÍTICAS},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Environment for education on Industry 4.0},

author = {Juan J Fuertes and Miguel A Prada and José Ramón Rodríguez-Ossorio and Raúl González-Herbón and Daniel Pérez and Manuel Domínguez},

doi = {10.1109/ACCESS.2021.3120517},

issn = {2169-3536},

year  = {2021},

date = {2021-10-15},

urldate = {2021-10-15},

journal = {IEEE Access},

pages = {144395-144405},

keywords = {AUTOMATIZACIÓN CONTROL Y SUPERVISIÓN INDUSTRIAL, INDUSTRIA 4.0, LABORATORIOS VIRTUALES Y REMOTOS},

pubstate = {published},

tppubtype = {article}

}

@article{alonso21,

title = {Virtual Sensor for Probabilistic Estimation of the Evaporation in Cooling Towers},

author = {Serafín Alonso and Antonio Morán and Daniel Pérez and Miguel A Prada and Juan J Fuertes and Manuel Domínguez},

doi = {10.3233/ICA-210654},

year  = {2021},

date = {2021-08-27},

journal = {Integrated Computer-Aided Engineering},

volume = {28},

number = {4},

pages = {369-381},

keywords = {INDUSTRIA 4.0, MACHINE LEARNING, SUPERVISIÓN ENERGÉTICA EN EDIFICIOS},

pubstate = {published},

tppubtype = {article}

}

@article{GarciaPerez2021,

title = {Fully-Convolutional Denoising Auto-Encoders for NILM in Large Non-Residential Buildings},

author = {Diego García and Daniel Pérez and Ignacio Díaz and Ana González and Manuel Domínguez and Abel A Cuadrado},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85099087289&doi=10.1109%2fTSG.2020.3047712&partnerID=40&md5=3de9b98c830097ee3f4a848db27d3a72},

doi = {10.1109/TSG.2020.3047712},

year  = {2021},

date = {2021-01-01},

urldate = {2021-01-01},

journal = {IEEE Transactions on Smart Grid},

volume = {12},

number = {3},

pages = {2722 – 2731},

note = {Cited by: 38},

keywords = {MACHINE LEARNING, SUPERVISIÓN ENERGÉTICA EN EDIFICIOS},

pubstate = {published},

tppubtype = {article}

}

@article{perez20d,

title = {Evaluation of feature learning for anomaly detection in network traffic},

author = {Daniel Pérez and Serafín Alonso and Antonio Morán and Miguel A Prada and Juan J Fuertes and Manuel Domínguez},

doi = {10.1007/s12530-020-09342-5},

year  = {2020},

date = {2020-04-22},

journal = {Evolving Systems},

publisher = {Springer},

keywords = {CIBERSEGURIDAD EN INFRAESTRUCTURAS CRÍTICAS, MACHINE LEARNING},

pubstate = {published},

tppubtype = {article}

}

@article{alonso2020estimating,

title = {Estimating cooling production and monitoring efficiency in chillers using a soft sensor},

author = { Serafín Alonso and Antonio Morán and Daniel Pérez and Miguel A Prada and Ignacio Díaz and Manuel Domínguez},

doi = {10.1007/s00521-020-05165-2},

year  = {2020},

date = {2020-01-01},

journal = {Neural Computing and Applications},

volume = {32},

number = {23},

pages = {17291--17308},

publisher = {Springer London},

keywords = {MACHINE LEARNING, SUPERVISIÓN ENERGÉTICA EN EDIFICIOS},

pubstate = {published},

tppubtype = {article}

}

@article{moran2020feature,

title = {Feature Extraction from Building Submetering Networks Using Deep Learning},

author = { Antonio Morán and Serafín Alonso and Daniel Pérez and Miguel A Prada and Juan J Fuertes and Manuel Domínguez},

doi = {10.3390/s20133665},

year  = {2020},

date = {2020-01-01},

journal = {Sensors},

volume = {20},

number = {13},

pages = {3665},

publisher = {Multidisciplinary Digital Publishing Institute},

keywords = {MACHINE LEARNING, SUPERVISIÓN ENERGÉTICA EN EDIFICIOS},

pubstate = {published},

tppubtype = {article}

}

@article{Alonso2019c,

title = {A deep learning approach for fusing sensor data from screw compressors},

author = {Serafín Alonso and Daniel Pérez and Juan J Fuertes and Ignacio Díaz and Manuel Domínguez },

doi = {10.3390/s19132868},

issn = {1424-8220},

year  = {2019},

date = {2019-09-01},

journal = {Sensors},

volume = {19},

number = {13},

keywords = {AUTOMATIZACIÓN CONTROL Y SUPERVISIÓN INDUSTRIAL, MACHINE LEARNING, SUPERVISIÓN ENERGÉTICA EN EDIFICIOS},

pubstate = {published},

tppubtype = {article}

}

@article{Domínguez2019b,

title = {Experimentation environment for industrial control systems cybersecurity: On-site and remote training},

author = {Manuel Domínguez and Antonio Morán and Serafín Alonso and Miguel A Prada and Daniel Pérez and Juan J Fuertes },

doi = {10.1016/j.ifacol.2019.08.209},

year  = {2019},

date = {2019-08-16},

journal = {IFAC-PapersOnLine},

volume = {52},

number = {9},

pages = {278-284},

keywords = {AUTOMATIZACIÓN CONTROL Y SUPERVISIÓN INDUSTRIAL, CIBERSEGURIDAD EN INFRAESTRUCTURAS CRÍTICAS, INDUSTRIA 4.0},

pubstate = {published},

tppubtype = {article}

}

@article{García2018,

title = {Interactive visualization for NILM in large buildings using non-negative matrix factorization},

author = {Diego García and Ignacio Díaz and Daniel Pérez and Abel A Cuadrado and Manuel Domínguez and Antonio Morán},

doi = {10.1016/j.enbuild.2018.06.058},

issn = {0378-7788},

year  = {2018},

date = {2018-10-01},

journal = {Energy and Buildings},

volume = {176},

pages = {95 - 108},

keywords = {MACHINE LEARNING, SUPERVISIÓN ENERGÉTICA EN EDIFICIOS},

pubstate = {published},

tppubtype = {article}

}

@article{diaz2017,

title = {Energy analytics in public buildings using interactive histograms},

author = {Ignacio Díaz and Abel A Cuadrado and Daniel Pérez and Manuel Domínguez and Serafín Alonso and Miguel A Prada},

doi = {10.1016/j.enbuild.2016.10.026},

issn = {0378-7788},

year  = {2017},

date = {2017-01-01},

journal = {Energy and Buildings},

volume = {134},

pages = {94--104},

publisher = {Elsevier},

keywords = {MACHINE LEARNING, SUPERVISIÓN ENERGÉTICA EN EDIFICIOS},

pubstate = {published},

tppubtype = {article}

}

@article{perez2013visual,

title = {Visual analysis of a cold rolling process using a dimensionality reduction approach},

author = {Daniel Pérez and Francisco J García and Ignacio Díaz and Abel A Cuadrado and Daniel G Ordóñez and Alberto B Díez and Manuel Domínguez},

doi = {10.1016/j.engappai.2013.05.009},

year  = {2013},

date = {2013-01-01},

journal = {Engineering Applications of Artificial Intelligence},

volume = {26},

number = {8},

pages = {1865--1871},

publisher = {Elsevier},

keywords = {MACHINE LEARNING},

pubstate = {published},

tppubtype = {article}

}