Eva Portillo
Orcid: 0000-0002-1026-3248
According to our database1,
Eva Portillo
authored at least 32 papers
between 2007 and 2023.
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Bibliography
2023
PLAHS: A Partial Labelling Autonomous Hyper-heuristic System for Industry 4.0 with application on classification of cold stamping process.
Appl. Soft Comput., November, 2023
Machine learning-based gait anomaly detection using a sensorized tip: an individualized approach.
Neural Comput. Appl., August, 2023
2022
Influence of statistical feature normalisation methods on K-Nearest Neighbours and K-Means in the context of industry 4.0.
Eng. Appl. Artif. Intell., 2022
A hyper-heuristic inspired approach for automatic failure prediction in the context of industry 4.0.
Comput. Ind. Eng., 2022
2021
Soft-Sensor for Class Prediction of the Percentage of Pentanes in Butane at a Debutanizer Column.
Sensors, 2021
A heuristic approach for lactate threshold estimation for training decision-making: An accessible and easy to use solution for recreational runners.
Eur. J. Oper. Res., 2021
Soft-sensor design for vacuum distillation bottom product penetration classification.
Appl. Soft Comput., 2021
Normalization Influence on ANN-Based Models Performance: A New Proposal for Features' Contribution Analysis.
IEEE Access, 2021
2020
Pulsewidth Modulation-Based Algorithm for Spike Phase Encoding and Decoding of Time-Dependent Analog Data.
IEEE Trans. Neural Networks Learn. Syst., 2020
A Machine Learning Approach to Perform Physical Activity Classification Using a Sensorized Crutch Tip.
IEEE Access, 2020
2019
Analysis and Application of Normalization Methods with Supervised Feature Weighting to Improve K-means Accuracy.
Proceedings of the 14th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2019), 2019
A Novel Heuristic Approach for the Simultaneous Selection of the Optimal Clustering Method and Its Internal Parameters for Time Series Data.
Proceedings of the 14th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2019), 2019
2018
Real time direct kinematic problem computation of the 3PRS robot using neural networks.
Neurocomputing, 2018
Estimation of lactate threshold with machine learning techniques in recreational runners.
Appl. Soft Comput., 2018
2017
Recurrent ANN-based modelling of the dynamic evolution of the surface roughness in grinding.
Neural Comput. Appl., 2017
Downsizing training data with weighted FCM for predicting the evolution of specific grinding energy with RNNs.
Appl. Soft Comput., 2017
2016
A new approach for dynamic modelling of energy consumption in the grinding process using recurrent neural networks.
Neural Comput. Appl., 2016
2015
Proceedings of the 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2015
Proceedings of the Engineering Applications of Neural Networks, 2015
2014
Virtual Sensors for On-line Wheel Wear and Part Roughness Measurement in the Grinding Process.
Sensors, 2014
2012
Int. J. Comput. Integr. Manuf., 2012
Towards an Infrastructure Model for Composing and Reconfiguring Cyber-Physical Systems.
Proceedings of the Ubiquitous Computing and Ambient Intelligence, 2012
Proceedings of the 1st Conference on Embedded Systems, 2012
2010
Proceedings of 15th IEEE International Conference on Emerging Technologies and Factory Automation, 2010
2009
Recurrent ANN for monitoring degraded behaviours in a range of workpiece thicknesses.
Eng. Appl. Artif. Intell., 2009
Proceedings of the 10th European Control Conference, 2009
2008
Artificial Neural Networks for detecting instability trends in different workpiece thicknesses in a machining process.
Proceedings of the American Control Conference, 2008
2007
IEEE Trans. Instrum. Meas., 2007
On the application of recurrent neural network techniques for detecting instability trends in an industrial process.
Proceedings of 12th IEEE International Conference on Emerging Technologies and Factory Automation, 2007