Inés María Galván

Publication Activity (10 Years)

Years Active: 1997-2023
Publications (10 Years): 16

Top Topics

Portfolio Optimization

Forecasting Model

Prediction Intervals

Top Venues

Appl. Soft Comput.

Comput. Informatics

Publications

Antonio Alcántara, Inés María Galván, Ricardo Aler
Pareto Optimal Prediction Intervals with Hypernetworks. Appl. Soft Comput. 133 (2023)
Miguel López-Cuesta, Ricardo Aler, Inés María Galván, Francisco J. Rodríguez-Benítez, David Pozo-Vázquez
Improving Solar Radiation Nowcasts by Blending Data-Driven, Satellite-Images-Based and All-Sky-Imagers-Based Models Using Machine Learning Techniques. Remote. Sens. 15 (9) (2023)
Esteban García-Cuesta, Ricardo Aler, David Pozo-Vázquez, Inés María Galván
A combination of supervised dimensionality reduction and learning methods to forecast solar radiation. Appl. Intell. 53 (11) (2023)
Antonio Alcántara, Inés María Galván, Ricardo Aler
Deep neural networks for the quantile estimation of regional renewable energy production. Appl. Intell. 53 (7) (2023)
Antonio Alcántara, Inés María Galván, Ricardo Aler
Direct estimation of prediction intervals for solar and wind regional energy forecasting with deep neural networks. Eng. Appl. Artif. Intell. 114 (2022)
Javier Huertas-Tato, Inés María Galván, Ricardo Aler, Francisco J. Rodríguez-Benítez, David Pozo-Vázquez
Using a Multi-view Convolutional Neural Network to monitor solar irradiance. Neural Comput. Appl. 34 (13) (2022)
José María Valls, Ricardo Aler, Inés María Galván, David Camacho
Supervised data transformation and dimensionality reduction with a 3-layer multi-layer perceptron for classification problems. J. Ambient Intell. Humaniz. Comput. 12 (12) (2021)
Inés María Galván, Javier Huertas-Tato, Francisco J. Rodríguez-Benítez, Clara Arbizu-Barrena, David Pozo-Vázquez, Ricardo Aler
Evolutionary-based prediction interval estimation by blending solar radiation forecasting models using meteorological weather types. Appl. Soft Comput. 109 (2021)
Javier Huertas-Tato, Ricardo Aler, Francisco J. Rodríguez-Benítez, Clara Arbizu-Barrena, David Pozo-Vázquez, Inés María Galván
Predicting Global Irradiance Combining Forecasting Models Through Machine Learning. HAIS (2018)
Rubén Martín-Vázquez, Ricardo Aler, Inés María Galván
Wind Energy Forecasting at Different Time Horizons with Individual and Global Models. AIAI (2018)
Rubén Martín-Vázquez, Javier Huertas-Tato, Ricardo Aler, Inés María Galván
Studying the Effect of Measured Solar Power on Evolutionary Multi-objective Prediction Intervals. IDEAL (2) (2018)
Kaouter Labed, Fizazi Hadria, Habib Mahi, Inés María Galván
A Comparative Study of Classical Clustering Method and Cuckoo Search Approach for Satellite Image Clustering: Application to Water Body Extraction. Appl. Artif. Intell. 32 (1) (2018)
Ricardo Martín, Ricardo Aler, Inés María Galván
A filter attribute selection method based on local reliable information. Appl. Intell. 48 (1) (2018)
Inés María Galván, José María Valls, Alejandro Cervantes, Ricardo Aler
Multi-objective evolutionary optimization of prediction intervals for solar energy forecasting with neural networks. Inf. Sci. 418 (2017)
Rubén Martín-Vázquez, Ricardo Aler, Inés María Galván
A Study on Feature Selection Methods for Wind Energy Prediction. IWANN (1) (2017)
R. Martin, Ricardo Aler, José María Valls, Inés María Galván
Machine learning techniques for daily solar energy prediction and interpolation using numerical weather models. Concurr. Comput. Pract. Exp. 28 (4) (2016)
Ricardo Aler, Inés María Galván
Optimizing the number of electrodes and spatial filters for Brain-Computer Interfaces by means of an evolutionary multi-objective approach. Expert Syst. Appl. 42 (15-16) (2015)
Sandra García-Rodríguez, David Quintana, Inés María Galván, Pedro Isasi
Extended mean-variance model for reliable evolutionary portfolio optimization. AI Commun. 27 (3) (2014)
Ricardo Aler, Ricardo Martín, José María Valls, Inés María Galván
A Study of Machine Learning Techniques for Daily Solar Energy Forecasting Using Numerical Weather Models. IDC (2014)
Sandra García-Rodríguez, David Quintana, Inés María Galván, Pedro Isasi
Multiobjective Algorithms with Resampling for Portfolio Optimization. Comput. Informatics 32 (4) (2013)
Sandra García-Rodríguez, David Quintana, Inés María Galván, Pedro Isasi
Time-stamped resampling for robust evolutionary portfolio optimization. Expert Syst. Appl. 39 (12) (2012)
Ricardo Aler, Inés María Galván, José María Valls
Applying evolution strategies to preprocessing EEG signals for brain-computer interfaces. Inf. Sci. 215 (2012)
Esteban García-Cuesta, Inés María Galván, Antonio J. de Castro
Recursive Discriminant Regression Analysis to Find Homogeneous Groups. Int. J. Neural Syst. 21 (1) (2011)
Inés María Galván, José María Valls, Miguel García, Pedro Isasi
A lazy learning approach for building classification models. Int. J. Intell. Syst. 26 (8) (2011)
Sandra García-Rodríguez, David Quintana, Inés María Galván, Pedro Isasi
Portfolio Optimization Using SPEA2 with Resampling. IDEAL (2011)
Sandra García-Rodríguez, Ricardo Aler, Inés María Galván
Using Evolutionary Multiobjective Techniques for Imbalanced Classification Data. ICANN (1) (2010)
Ricardo Aler, Inés María Galván, José María Valls
Evolving spatial and frequency selection filters for Brain-Computer Interfaces. IEEE Congress on Evolutionary Computation (2010)
Ricardo Aler, Inés María Galván, José María Valls
Improving Classification for Brain Computer Interfaces using Transitions and a Moving Window. BIOSIGNALS (2009)
Alejandro Cervantes, Inés María Galván, Pedro Isasi Viñuela
Michigan Particle Swarm Optimization for Prototype Reduction in Classification Problems. New Gener. Comput. 27 (3) (2009)
Sandra García-Rodríguez, Cristóbal Luque, Alejandro Cervantes, Inés María Galván
Multiobjective Algorithms Hybridization to Optimize Broadcasting Parameters in Mobile Ad-Hoc Networks. IWANN (1) (2009)
Inés María Galván, José María Valls, Nicolas Lecomte, Pedro Isasi
A Lazy Approach for Machine Learning Algorithms. AIAI (2009)
Carlos Segura, Alejandro Cervantes, Antonio J. Nebro, María Dolores Jaraíz-Simón, Eduardo Segredo, Sandra García-Rodríguez, Francisco Luna, Juan Antonio Gómez Pulido, Gara Miranda, Cristóbal Luque, Enrique Alba, Miguel Ángel Vega Rodríguez, Coromoto León, Inés María Galván
Optimizing the DFCN Broadcast Protocol with a Parallel Cooperative Strategy of Multi-Objective Evolutionary Algorithms. EMO (2009)
Ricardo Aler, Inés María Galván, José María Valls
Transition Detection for Brain Computer Interface Classification. BIOSTEC (Selected Papers) (2009)
Esteban García-Cuesta, Inés María Galván, Antonio J. de Castro
Supervised clustering via principal component analysis in a retrieval application. KDD Workshop on Knowledge Discovery from Sensor Data (2009)
Esteban García-Cuesta, Inés María Galván, Antonio J. de Castro
Discriminant Regression Analysis to Find Homogeneous Structures. IDEAL (2009)
Alejandro Cervantes, Inés María Galván, Pedro Isasi
AMPSO: A New Particle Swarm Method for Nearest Neighborhood Classification. IEEE Trans. Syst. Man Cybern. Part B 39 (5) (2009)
José María Valls, Inés María Galván, Pedro Isasi Viñuela
Learning radial basis neural networks in a lazy way: A comparative study. Neurocomputing 71 (13-15) (2008)
Esteban García-Cuesta, Inés María Galván, Antonio J. de Castro
Multilayer perceptron as inverse model in a ground-based remote sensing temperature retrieval problem. Eng. Appl. Artif. Intell. 21 (1) (2008)
Alejandro Cervantes, Inés María Galván, Pedro Isasi
An Adaptive Michigan Approach PSO for Nearest Prototype Classification. IWINAC (2) (2007)
José María Valls, Inés María Galván, Pedro Isasi
LRBNN: A Lazy Radial Basis Neural Network model. AI Commun. 20 (2) (2007)
Alejandro Cervantes, Inés María Galván, Pedro Isasi
Building Nearest Prototype Classifiers Using a Michigan Approach PSO. SIS (2007)
Esteban García-Cuesta, Inés María Galván, Antonio J. de Castro
Spectral High Resolution Feature Selection for Retrieval of Combustion Temperature Profiles. IDEAL (2006)
José María Valls, Inés María Galván, Pedro Isasi Viñuela
Improving the Generalization Ability of RBNN Using a Selective Strategy Based on the Gaussian Kernel Function. Comput. Artif. Intell. 25 (1) (2006)
José María Valls, Inés María Galván, Pedro Isasi
Lazy Training of Radial Basis Neural Networks. ICANN (1) (2006)
Alejandro Cervantes, Inés María Galván, Pedro Isasi
A comparison between the Pittsburgh and Michigan approaches for the binary PSO algorithm. Congress on Evolutionary Computation (2005)
Esteban García-Cuesta, Inés María Galván, Antonio J. de Castro
Neural Networks and Spectral Feature Selection for Retrieval of Hot Gases Temperature Profiles. CIMCA/IAWTIC (2005)
Germán Gutiérrez, Araceli Sanchis, Pedro Isasi Viñuela, José M. Molina, Inés María Galván
Non-Direct Encoding Method Based on Cellular Automata to Design Neural Network Architectures. Comput. Artif. Intell. 24 (3) (2005)
César Estébanez, José María Valls, Ricardo Aler, Inés María Galván
A First Attempt at Constructing Genetic Programming Expressions for EEG Classification. ICANN (1) (2005)
José María Valls, Inés María Galván, Pedro Isasi
Lazy Learning in Radial Basis Neural Networks: A Way of Achieving More Accurate Models. Neural Process. Lett. 20 (2) (2004)
Pedro Isasi, José María Valls, Inés María Galván
A Better Selection of Patterns in Lazy Learning Radial Basis Neural Networks. IWANN (1) (2003)
Juan Manuel Alonso-Weber, Inés María Galván, Araceli Sanchis de Miguel
Modified Self-organizing Maps for Line Extraction in Digitized Text Documents. Applied Informatics (2003)
José María Valls, Inés María Galván, Pedro Isasi
How the Selection of Training Patterns can Improve the Generalization Capability in Radial Basis Neural Networks. Applied Informatics (2003)
Germán Gutiérrez, Inés María Galván, José M. Molina, Araceli Sanchis
Generative Capacities of Cellular Automata Codification for Evolution of NN Codification. ICANN (2002)
M. A. Guinea, Germán Gutiérrez, Inés María Galván, Araceli Sanchis, José M. Molina
Generative capacities of grammars codification for evolution of NN architectures. IEEE Congress on Evolutionary Computation (2002)
José M. Molina, Inés María Galván, José María Valls, Andrés Leal
Optimizing the Number of Learning Cycles in the Design of Radial Basis Neural Networks Using a Multi-Agent System. Comput. Artif. Intell. 20 (5) (2001)
José María Valls, Pedro Isasi, Inés María Galván
Deferring the Learning for Better Generalization in Radial Basis Neural Networks. ICANN (2001)
Inés María Galván, Pedro Isasi, Ricardo Aler, José María Valls
A Selective Learning Method to Improve the Generalization of Multilayer Feedforward Neural Networks. Int. J. Neural Syst. 11 (2) (2001)
Inés María Galván, Pedro Isasi
Multi-step Learning Rule for Recurrent Neural Models: An Application to Time Series Forecasting. Neural Process. Lett. 13 (2) (2001)
Germán Gutiérrez, Pedro Isasi, José M. Molina, Araceli Sanchis, Inés María Galván
Evolutionary Cellular Configurations for Designing Feed-Forward Neural Networks Architectures. IWANN (1) (2001)
José M. Molina, Inés María Galván, Pedro Isasi, Araceli Sanchis
Grammars and cellular automata for evolving neural networks architectures. SMC (2000)
José María Valls, José M. Molina, Inés María Galván
Sistema Multiagente para el diseño de Redes de Neuronas de Base Radial Óptimas. Inteligencia Artif. 4 (10) (2000)
D. Barrios, Inés María Galván, P. Jsasi, J. Ríos
Improving Inverse Control on Real Time by Means of Neural Networks. ICONIP (2) (1997)