Pedro Antonio Gutiérrez

Orcid: 0000-0002-2657-776X

Affiliations:
  • University of Córdoba, Department of Computer Science and Numerical Analysis, Spain
  • University of Granada, Spain


According to our database1, Pedro Antonio Gutiérrez authored at least 191 papers between 2006 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2025
CNN explanation methods for ordinal regression tasks.
Neurocomputing, 2025

2024
Deep Ordinal Classification in Forest Areas Using Light Detection and Ranging Point Clouds.
Sensors, April, 2024

EBANO: A novel Ensemble BAsed on uNimodal Ordinal classifiers for the prediction of significant wave height.
Knowl. Based Syst., 2024

A general explicable forecasting framework for weather events based on ordinal classification and inductive rules combined with fuzzy logic.
Knowl. Based Syst., 2024

Fusion of standard and ordinal dropout techniques to regularise deep models.
Inf. Fusion, 2024

ORFEO: Ordinal classifier and Regressor Fusion for Estimating an Ordinal categorical target.
Eng. Appl. Artif. Intell., 2024

dlordinal: a Python package for deep ordinal classification.
CoRR, 2024

Improving the classification of extreme classes by means of loss regularisation and generalised beta distributions.
CoRR, 2024

Energy Flux Prediction Using an Ordinal Soft Labelling Strategy.
Proceedings of the Bioinspired Systems for Translational Applications: From Robotics to Social Engineering, 2024

Medium- and Long-Term Wind Speed Prediction Using the Multi-task Learning Paradigm.
Proceedings of the Bioinspired Systems for Translational Applications: From Robotics to Social Engineering, 2024

Age Estimation Using Soft Labelling Ordinal Classification Approaches.
Proceedings of the Advances in Artificial Intelligence, 2024

Multivariate-Autoencoder Flow-Analogue Method for Heat Waves Reconstruction.
Proceedings of the Advances in Artificial Intelligence, 2024

O-Hydra: A Hybrid Convolutional and Dictionary-Based Approach to Time Series Ordinal Classification.
Proceedings of the Advances in Artificial Intelligence, 2024

2023
Generalised triangular distributions for ordinal deep learning: Novel proposal and optimisation.
Inf. Sci., November, 2023

Error-Correcting Output Codes in the Framework of Deep Ordinal Classification.
Neural Process. Lett., October, 2023

Cluster analysis and forecasting of viruses incidence growth curves: Application to SARS-CoV-2.
Expert Syst. Appl., September, 2023

Soft labelling based on triangular distributions for ordinal classification.
Inf. Fusion, May, 2023

Exponential loss regularisation for encouraging ordinal constraint to shotgun stocks quality assessment.
Appl. Soft Comput., May, 2023

Activation Functions for Convolutional Neural Networks: Proposals and Experimental Study.
IEEE Trans. Neural Networks Learn. Syst., March, 2023

A hybrid feature learning approach based on convolutional kernels for ATM fault prediction using event-log data.
Eng. Appl. Artif. Intell., 2023

Convolutional and Deep Learning based techniques for Time Series Ordinal Classification.
CoRR, 2023

Deep learning based hierarchical classifier for weapon stock aesthetic quality control assessment.
Comput. Ind., 2023

Gramian Angular and Markov Transition Fields Applied to Time Series Ordinal Classification.
Proceedings of the Advances in Computational Intelligence, 2023

Ordinal Classification Approach for Donor-Recipient Matching in Liver Transplantation with Circulatory Death Donors.
Proceedings of the Advances in Computational Intelligence, 2023

Evaluating the Performance of Explanation Methods on Ordinal Regression CNN Models.
Proceedings of the Advances in Computational Intelligence, 2023

A Dictionary-Based Approach to Time Series Ordinal Classification.
Proceedings of the Advances in Computational Intelligence, 2023

2022
Unimodal regularisation based on beta distribution for deep ordinal regression.
Pattern Recognit., 2022

A novel deep ordinal classification approach for aesthetic quality control classification.
Neural Comput. Appl., 2022

COVID-19 contagion forecasting framework based on curve decomposition and evolutionary artificial neural networks: A case study in Andalusia, Spain.
Expert Syst. Appl., 2022

Predictive Maintenance of ATM Machines by Modelling Remaining Useful Life with Machine Learning Techniques.
Proceedings of the 17th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2022), 2022

Assessing the Efficient Market Hypothesis for Cryptocurrencies with High-Frequency Data Using Time Series Classification.
Proceedings of the 17th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2022), 2022

Clustering of COVID-19 Time Series Incidence Intensity in Andalusia, Spain.
Proceedings of the Bio-inspired Systems and Applications: from Robotics to Ambient Intelligence, 2022

Gamifying the Classroom for the Acquisition of Skills Associated with Machine Learning: A Two-Year Case Study.
Proceedings of the International Joint Conference 15th International Conference on Computational Intelligence in Security for Information Systems (CISIS 2022) 13th International Conference on EUropean Transnational Education (ICEUTE 2022), 2022

2021
Time-Series Clustering Based on the Characterization of Segment Typologies.
IEEE Trans. Cybern., 2021

An ordinal CNN approach for the assessment of neurological damage in Parkinson's disease patients.
Expert Syst. Appl., 2021

Enhancing the ORCA framework with a new Fuzzy Rule Base System implementation compatible with the JFML library.
Proceedings of the 30th IEEE International Conference on Fuzzy Systems, 2021

ReLU-Based Activations: Analysis and Experimental Study for Deep Learning.
Proceedings of the Advances in Artificial Intelligence, 2021

Studying the Effect of Different L<sub>p</sub> Norms in the Context of Time Series Ordinal Classification.
Proceedings of the Advances in Artificial Intelligence, 2021

2020
Ordinal Multi-class Architecture for Predicting Wind Power Ramp Events Based on Reservoir Computing.
Neural Process. Lett., 2020

Multi-task learning for the prediction of wind power ramp events with deep neural networks.
Neural Networks, 2020

Prediction of convective clouds formation using evolutionary neural computation techniques.
Neural Comput. Appl., 2020

Cumulative link models for deep ordinal classification.
Neurocomputing, 2020

Optimising Convolutional Neural Networks using a Hybrid Statistically-driven Coral Reef Optimisation algorithm.
Appl. Soft Comput., 2020

Ordinal Versus Nominal Time Series Classification.
Proceedings of the Advanced Analytics and Learning on Temporal Data, 2020

Time series ordinal classification via shapelets.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Statistically-driven Coral Reef metaheuristic for automatic hyperparameter setting and architecture design of Convolutional Neural Networks.
Proceedings of the IEEE Congress on Evolutionary Computation, 2020

2019
Editorial: Booming of Neural Networks and Learning Systems.
IEEE Trans. Neural Networks Learn. Syst., 2019

OCAPIS: R package for Ordinal Classification and Preprocessing in Scala.
Prog. Artif. Intell., 2019

Dynamical memetization in coral reef optimization algorithms for optimal time series approximation.
Prog. Artif. Intell., 2019

ORCA: A Matlab/Octave Toolbox for Ordinal Regression.
J. Mach. Learn. Res., 2019

On the use of evolutionary time series analysis for segmenting paleoclimate data.
Neurocomputing, 2019

A hybrid dynamic exploitation barebones particle swarm optimisation algorithm for time series segmentation.
Neurocomputing, 2019

Monotonic classification: An overview on algorithms, performance measures and data sets.
Neurocomputing, 2019

Deep ordinal classification based on cumulative link models.
CoRR, 2019

Multi-objective evolutionary optimization using the relationship between F 1 and accuracy metrics in classification tasks.
Appl. Intell., 2019

Deep Ordinal Classification Based on the Proportional Odds Model.
Proceedings of the From Bioinspired Systems and Biomedical Applications to Machine Learning, 2019

Modelling Survival by Machine Learning Methods in Liver Transplantation: Application to the UNOS Dataset.
Proceedings of the Intelligent Data Engineering and Automated Learning - IDEAL 2019, 2019

A Hybrid Approach to Time Series Classification with Shapelets.
Proceedings of the Intelligent Data Engineering and Automated Learning - IDEAL 2019, 2019

2018
Time series forecasting by recurrent product unit neural networks.
Neural Comput. Appl., 2018

Simultaneous optimisation of clustering quality and approximation error for time series segmentation.
Inf. Sci., 2018

Time series clustering based on the characterisation of segment typologies.
CoRR, 2018

Partial order label decomposition approaches for melanoma diagnosis.
Appl. Soft Comput., 2018

A statistically-driven Coral Reef Optimization algorithm for optimal size reduction of time series.
Appl. Soft Comput., 2018

A mixture of experts model for predicting persistent weather patterns.
Proceedings of the 2018 International Joint Conference on Neural Networks, 2018

Distribution-Based Discretisation and Ordinal Classification Applied to Wave Height Prediction.
Proceedings of the Intelligent Data Engineering and Automated Learning - IDEAL 2018, 2018

Wind Power Ramp Events Ordinal Prediction Using Minimum Complexity Echo State Networks.
Proceedings of the Intelligent Data Engineering and Automated Learning - IDEAL 2018, 2018

An Empirical Validation of a New Memetic CRO Algorithm for the Approximation of Time Series.
Proceedings of the Advances in Artificial Intelligence, 2018

Hybrid Weighted Barebones Exploiting Particle Swarm Optimization Algorithm for Time Series Representation.
Proceedings of the Bioinspired Optimization Methods and Their Applications, 2018

2017
Identification of extreme wave heights with an evolutionary algorithm in combination with a likelihood-based segmentation.
Prog. Artif. Intell., 2017

Identifying Market Behaviours Using European Stock Index Time Series by a Hybrid Segmentation Algorithm.
Neural Process. Lett., 2017

Synthetic semi-supervised learning in imbalanced domains: Constructing a model for donor-recipient matching in liver transplantation.
Knowl. Based Syst., 2017

Dynamically weighted evolutionary ordinal neural network for solving an imbalanced liver transplantation problem.
Artif. Intell. Medicine, 2017

Estimating Rodent Brain Volume by a Deformable Contour Model.
Proceedings of the Medical Image Understanding and Analysis - 21st Annual Conference, 2017

An Iterated Greedy Algorithm for Improving the Generation of Synthetic Patterns in Imbalanced Learning.
Proceedings of the Advances in Computational Intelligence, 2017

Class Switching Ensembles for Ordinal Regression.
Proceedings of the Advances in Computational Intelligence, 2017

A Coral Reef Optimization Algorithm for Wave Height Time Series Segmentation Problems.
Proceedings of the Advances in Computational Intelligence, 2017

Combining Reservoir Computing and Over-Sampling for Ordinal Wind Power Ramp Prediction.
Proceedings of the Advances in Computational Intelligence, 2017

2016
Oversampling the Minority Class in the Feature Space.
IEEE Trans. Neural Networks Learn. Syst., 2016

Machine Learning Methods for Binary and Multiclass Classification of Melanoma Thickness From Dermoscopic Images.
IEEE Trans. Medical Imaging, 2016

Ordinal Regression Methods: Survey and Experimental Study.
IEEE Trans. Knowl. Data Eng., 2016

Current prospects on ordinal and monotonic classification.
Prog. Artif. Intell., 2016

A Study on Multi-Scale Kernel Optimisation via Centered Kernel-Target Alignment.
Neural Process. Lett., 2016

On the Use of Nominal and Ordinal Classifiers for the Discrimination of States of Development in Fish Oocytes.
Neural Process. Lett., 2016

Semi-supervised learning for ordinal Kernel Discriminant Analysis.
Neural Networks, 2016

Selecting patterns and features for between- and within- crop-row weed mapping using UAV-imagery.
Expert Syst. Appl., 2016

Adapting linear discriminant analysis to the paradigm of learning from label proportions.
Proceedings of the 2016 IEEE Symposium Series on Computational Intelligence, 2016

Machine learning paradigms for weed mapping via unmanned aerial vehicles.
Proceedings of the 2016 IEEE Symposium Series on Computational Intelligence, 2016

Hybridization of neural network models for the prediction of Extreme Significant Wave Height segments.
Proceedings of the 2016 IEEE Symposium Series on Computational Intelligence, 2016

Tackling the ordinal and imbalance nature of a melanoma image classification problem.
Proceedings of the 2016 International Joint Conference on Neural Networks, 2016

Representing ordinal input variables in the context of ordinal classification.
Proceedings of the 2016 International Joint Conference on Neural Networks, 2016

Classification of Melanoma Presence and Thickness Based on Computational Image Analysis.
Proceedings of the Hybrid Artificial Intelligent Systems - 11th International Conference, 2016

Fisher Score-Based Feature Selection for Ordinal Classification: A Social Survey on Subjective Well-Being.
Proceedings of the Hybrid Artificial Intelligent Systems - 11th International Conference, 2016

Time Series Representation by a Novel Hybrid Segmentation Algorithm.
Proceedings of the Hybrid Artificial Intelligent Systems - 11th International Conference, 2016

Ordinal Evolutionary Artificial Neural Networks for Solving an Imbalanced Liver Transplantation Problem.
Proceedings of the Hybrid Artificial Intelligent Systems - 11th International Conference, 2016

Learning from Label Proportions via an Iterative Weighting Scheme and Discriminant Analysis.
Proceedings of the Advances in Artificial Intelligence, 2016

On the Use of the Beta Distribution for a Hybrid Time Series Segmentation Algorithm.
Proceedings of the Advances in Artificial Intelligence, 2016

Multiclass Prediction of Wind Power Ramp Events Combining Reservoir Computing and Support Vector Machines.
Proceedings of the Advances in Artificial Intelligence, 2016

2015
Graph-Based Approaches for Over-Sampling in the Context of Ordinal Regression.
IEEE Trans. Knowl. Data Eng., 2015

The Benefits of Modeling Slack Variables in SVMs.
Neural Comput., 2015

Kernelising the Proportional Odds Model through kernel learning techniques.
Neurocomputing, 2015

Classification of countries' progress toward a knowledge economy based on machine learning classification techniques.
Expert Syst. Appl., 2015

Significant wave height and energy flux range forecast with machine learning classifiers.
Eng. Appl. Artif. Intell., 2015

A semi-supervised system for weed mapping in sunflower crops using unmanned aerial vehicles and a crop row detection method.
Appl. Soft Comput., 2015

An Experimental Comparison for the Identification of Weeds in Sunflower Crops via Unmanned Aerial Vehicles and Object-Based Analysis.
Proceedings of the Advances in Computational Intelligence, 2015

Energy Flux Range Classification by Using a Dynamic Window Autoregressive Model.
Proceedings of the Advances in Computational Intelligence, 2015

Applying a Hybrid Algorithm to the Segmentation of the Spanish Stock Market Index Time Series.
Proceedings of the Advances in Computational Intelligence, 2015

Nonlinear Ordinal Logistic Regression Using Covariates Obtained by Radial Basis Function Neural Networks Models.
Proceedings of the Advances in Computational Intelligence, 2015

Overcoming the Linearity of Ordinal Logistic Regression Adding Non-linear Covariates from Evolutionary Hybrid Neural Network Models.
Proceedings of the Advances in Artificial Intelligence, 2015

2014
Projection-Based Ensemble Learning for Ordinal Regression.
IEEE Trans. Cybern., 2014

Object-Based Image Classification of Summer Crops with Machine Learning Methods.
Remote. Sens., 2014

Ordinal regression neural networks based on concentric hyperspheres.
Neural Networks, 2014

Classification of EU countries' progress towards sustainable development based on ordinal regression techniques.
Knowl. Based Syst., 2014

Metrics to guide a multi-objective evolutionary algorithm for ordinal classification.
Neurocomputing, 2014

Special issue: Advances in learning schemes for function approximation.
Neurocomputing, 2014

Addressing remitting behavior using an ordinal classification approach.
Expert Syst. Appl., 2014

Simultaneous modelling of rainfall occurrence and amount using a hierarchical nominal-ordinal support vector classifier.
Eng. Appl. Artif. Intell., 2014

A guided data projection technique for classification of sovereign ratings: The case of European Union 27.
Appl. Soft Comput., 2014

Learning Kernel Label Decompositions for Ordinal Classification Problems.
Proceedings of the NCTA 2014 - Proceedings of the International Conference on Neural Computation Theory and Applications, part of IJCCI 2014, Rome, Italy, 22, 2014

Incorporating Privileged Information to Improve Manifold Ordinal Regression.
Proceedings of the NCTA 2014 - Proceedings of the International Conference on Neural Computation Theory and Applications, part of IJCCI 2014, Rome, Italy, 22, 2014

Time Series Segmentation of Paleoclimate Tipping Points by an Evolutionary Algorithm.
Proceedings of the Hybrid Artificial Intelligence Systems - 9th International Conference, 2014

Log-Gamma Distribution Optimisation via Maximum Likelihood for Ordered Probability Estimates.
Proceedings of the Hybrid Artificial Intelligence Systems - 9th International Conference, 2014

Support Vector Ordinal Regression using Privileged Information.
Proceedings of the 22th European Symposium on Artificial Neural Networks, 2014

2013
Negative Correlation Ensemble Learning for Ordinal Regression.
IEEE Trans. Neural Networks Learn. Syst., 2013

Generalised Gaussian radial basis function neural networks.
Soft Comput., 2013

Memetic Pareto differential evolutionary neural network used to solve an unbalanced liver transplantation problem.
Soft Comput., 2013

Exploitation of Pairwise Class Distances for Ordinal Classification.
Neural Comput., 2013

Ensembles of evolutionary product unit or RBF neural networks for the identification of sound for pass-by noise test in vehicles.
Neurocomputing, 2013

Improvement of accuracy in a sound synthesis method using Evolutionary Product Unit Networks.
Expert Syst. Appl., 2013

Ordinal and nominal classification of wind speed from synoptic pressurepatterns.
Eng. Appl. Artif. Intell., 2013

An n-Spheres Based Synthetic Data Generator for Supervised Classification.
Proceedings of the Advances in Computational Intelligence, 2013

Kernelizing the Proportional Odds Model through the Empirical Kernel Mapping.
Proceedings of the Advances in Computational Intelligence, 2013

Evolutionary Ordinal Extreme Learning Machine.
Proceedings of the Hybrid Artificial Intelligent Systems - 8th International Conference, 2013

Borderline Kernel Based Over-Sampling.
Proceedings of the Hybrid Artificial Intelligent Systems - 8th International Conference, 2013

Multi-scale Support Vector Machine Optimization by Kernel Target-Alignment.
Proceedings of the 21st European Symposium on Artificial Neural Networks, 2013

Synthetic over-sampling in the empirical feature space.
Proceedings of the 21st European Symposium on Artificial Neural Networks, 2013

2012
Evolutionary product unit neural networks for short-term wind speed forecasting in wind farms.
Neural Comput. Appl., 2012

A two-stage evolutionary algorithm based on sensitivity and accuracy for multi-class problems.
Inf. Sci., 2012

A Structural Distance-Based Crossover for Neural Network Classifiers.
Int. J. Pattern Recognit. Artif. Intell., 2012

Parameter estimation of q-Gaussian Radial Basis Functions Neural Networks with a Hybrid Algorithm for binary classification.
Neurocomputing, 2012

Permanent disability classification by combining evolutionary Generalized Radial Basis Function and logistic regression methods.
Expert Syst. Appl., 2012

Distribution of the search of evolutionary product unit neural networks for classification
CoRR, 2012

Approaching System Administration as a Group Project in Computer Engineering Higher Education.
Proceedings of the International Joint Conference CISIS'12-ICEUTE'12-SOCO'12 Special Sessions, 2012

Multiobjective Pareto Ordinal Classification for Predictive Microbiology.
Proceedings of the Soft Computing Models in Industrial and Environmental Applications, 2012

An ensemble approach for ordinal threshold models applied to liver transplantation.
Proceedings of the 2012 International Joint Conference on Neural Networks (IJCNN), 2012

An Experimental Study of Different Ordinal Regression Methods and Measures.
Proceedings of the Hybrid Artificial Intelligent Systems - 7th International Conference, 2012

Neural Network Ensembles to Determine Growth Multi-classes in Predictive Microbiology.
Proceedings of the Hybrid Artificial Intelligent Systems - 7th International Conference, 2012

Ordinal Classification Using Hybrid Artificial Neural Networks with Projection and Kernel Basis Functions.
Proceedings of the Hybrid Artificial Intelligent Systems - 7th International Conference, 2012

2011
Logistic Regression by Means of Evolutionary Radial Basis Function Neural Networks.
IEEE Trans. Neural Networks, 2011

A dynamic over-sampling procedure based on sensitivity for multi-class problems.
Pattern Recognit., 2011

Weighting Efficient Accuracy and Minimum Sensitivity for Evolving Multi-Class Classifiers.
Neural Process. Lett., 2011

Neuro-logistic Models Based on Evolutionary Generalized Radial Basis Function for the Microarray Gene Expression Classification Problem.
Neural Process. Lett., 2011

Evolutionary q-Gaussian radial basis function neural networks for multiclassification.
Neural Networks, 2011

MELM-GRBF: A modified version of the extreme learning machine for generalized radial basis function neural networks.
Neurocomputing, 2011

Memetic Pareto Evolutionary Artificial Neural Networks to determine growth/no-growth in predictive microbiology.
Appl. Soft Comput., 2011

Evolutionary q-Gaussian Radial Basis Function Neural Network to determine the microbial growth/no growth interface of Staphylococcus aureus.
Appl. Soft Comput., 2011

Sound Source Identification in Vehicles Using a Combined Linear-Evolutionary Product Unit Neural Network Model.
Proceedings of the Soft Computing Models in Industrial and Environmental Applications, 2011

Combining Evolutionary Generalized Radial Basis Function and Logistic Regression Methods for Classification.
Proceedings of the Soft Computing Models in Industrial and Environmental Applications, 2011

Hybrid Artificial Neural Networks: Models, Algorithms and Data.
Proceedings of the Advances in Computational Intelligence, 2011

Memetic Pareto Differential Evolutionary Neural Network for Donor-Recipient Matching in Liver Transplantation.
Proceedings of the Advances in Computational Intelligence, 2011

Numerical variable reconstruction from ordinal categories based on probability distributions.
Proceedings of the 11th International Conference on Intelligent Systems Design and Applications, 2011

Ordinal classification of depression spatial hot-spots of prevalence.
Proceedings of the 11th International Conference on Intelligent Systems Design and Applications, 2011

Evaluating nominal and ordinal classifiers for wind speed prediction from synoptic pressure patterns.
Proceedings of the 11th International Conference on Intelligent Systems Design and Applications, 2011

A preliminary study of ordinal metrics to guide a multi-objective evolutionary algorithm.
Proceedings of the 11th International Conference on Intelligent Systems Design and Applications, 2011

Permanent disability classification using hybrid neuro-logistic regression models.
Proceedings of the 2011 IEEE Workshop On Hybrid Intelligent Models And Applications, 2011

2010
Sensitivity versus accuracy in multiclass problems using memetic Pareto evolutionary neural networks.
IEEE Trans. Neural Networks, 2010

Designing multilayer perceptrons using a Guided Saw-tooth Evolutionary Programming Algorithm.
Soft Comput., 2010

Classification by evolutionary generalised radial basis functions.
Int. J. Hybrid Intell. Syst., 2010

A logistic radial basis function regression method for discrimination of cover crops in olive orchards.
Expert Syst. Appl., 2010

On the suitability of Extreme Learning Machine for gene classification using feature selection.
Proceedings of the 10th International Conference on Intelligent Systems Design and Applications, 2010

Ensemble determination using the TOPSIS decision support system in multi-objective evolutionary neural network classifiers.
Proceedings of the 10th International Conference on Intelligent Systems Design and Applications, 2010

Generalized Logistic Regression Models Using Neural Network Basis Functions Applied to the Detection of Banking Crises.
Proceedings of the Trends in Applied Intelligent Systems, 2010

Evolutionary <i>q</i>-Gaussian Radial Basis Functions for Improving Prediction Accuracy of Gene Classification Using Feature Selection.
Proceedings of the Artificial Neural Networks - ICANN 2010, 2010

Evolutionary <i>q</i>-Gaussian Radial Basis Functions for Binary-Classification.
Proceedings of the Hybrid Artificial Intelligence Systems, 5th International Conference, 2010

2009
Multilogistic Regression by Product Units.
Proceedings of the Encyclopedia of Artificial Intelligence (3 Volumes), 2009

Combined projection and kernel basis functions for classification in evolutionary neural networks.
Neurocomputing, 2009

A Sensitivity Clustering Method for Hybrid Evolutionary Algorithms.
Proceedings of the Methods and Models in Artificial and Natural Computation. A Homage to Professor Mira.s Scientific Legacy, 2009

Hyperbolic Tangent Basis Function Neural Networks Training by Hybrid Evolutionary Programming for Accurate Short-Term Wind Speed Prediction.
Proceedings of the Ninth International Conference on Intelligent Systems Design and Applications, 2009

A Sensitivity Clustering Method for Memetic Training of Radial Basis Function Neural Networks.
Proceedings of the Ninth International Conference on Intelligent Systems Design and Applications, 2009

Classification by Evolutionary Generalized Radial Basis Functions.
Proceedings of the Ninth International Conference on Intelligent Systems Design and Applications, 2009

MultiLogistic Regression using Initial and Radial Basis Function covariates.
Proceedings of the International Joint Conference on Neural Networks, 2009

Hybrid Multilogistic Regression by Means of Evolutionary Radial Basis Functions: Application to Precision Agriculture.
Proceedings of the Hybrid Artificial Intelligence Systems, 4th International Conference, 2009

Memetic Pareto Differential Evolution for Designing Artificial Neural Networks in Multiclassification Problems Using Cross-Entropy Versus Sensitivity.
Proceedings of the Hybrid Artificial Intelligence Systems, 4th International Conference, 2009

2008
Combined Projection and Kernel Basis Functions for Classification in Evolutionary Neural Networks.
Proceedings of the Innovations in Hybrid Intelligent Systems, 2008

Evolutionary product-unit neural networks classifiers.
Neurocomputing, 2008

Feature Selection for Hybrid Neuro-Logistic Regression Applied to Classification of Remote Sensed Data.
Proceedings of the 8th International Conference on Hybrid Intelligent Systems (HIS 2008), 2008

Memetic Pareto Evolutionary Artificial Neural Networks for the Determination of Growth Limits of Listeria Monocytogenes.
Proceedings of the 8th International Conference on Hybrid Intelligent Systems (HIS 2008), 2008

Evolutionary learning by a sensitivity-accuracy approach for multi-class problems.
Proceedings of the IEEE Congress on Evolutionary Computation, 2008

2007
Hybrid Evolutionary Algorithm with Product-Unit Neural Networks for Classification.
Proceedings of the Computational and Ambient Intelligence, 2007

Saw-Tooth Algorithm Guided by the Variance of Best Individual Distributions for Designing Evolutionary Neural Networks.
Proceedings of the Intelligent Data Engineering and Automated Learning, 2007

2006
Classification by means of Evolutionary Product-Unit Neural Networks.
Proceedings of the International Joint Conference on Neural Networks, 2006

Evolutionary Product-Unit Neural Networks for Classification.
Proceedings of the Intelligent Data Engineering and Automated Learning, 2006


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