Inés María Galván

发表

Generative Capacities of Cellular Automata Codification for Evolution of NN Codification

Araceli Sanchis, José M. Molina López, Germán Gutiérrez, 2002, ICANN.

Lazy Training of Radial Basis Neural Networks

Inés María Galván, José María Valls, Pedro Isasi Viñuela, 2006, ICANN.

Neural Networks and Spectral Feature Selection for Retrieval of Hot Gases Temperature Profiles

Inés María Galván, Esteban García-Cuesta, Antonio J. de Castro, 2005, International Conference on Computational Intelligence for Modelling, Control and Automation and International Conference on Intelligent Agents, Web Technologies and Internet Commerce (CIMCA-IAWTIC'06).

Portfolio Optimization Using SPEA2 with Resampling

Inés María Galván, Pedro Isasi Viñuela, Sandra García-Rodríguez, 2011, IDEAL.

Modified Self-organizing Maps for Line Extraction in Digitized Text Documents

Araceli Sanchis, Inés María Galván, Juan Manuel Alonso-Weber, 2003, Applied Informatics.

A Comparative Study of Classical Clustering Method and Cuckoo Search Approach for Satellite Image Clustering: Application to Water Body Extraction

Inés María Galván, Habib Mahi, Kaouter Labed, 2018, Appl. Artif. Intell..

Grammars and cellular automata for evolving neural networks architectures

Araceli Sanchis, José M. Molina López, Inés María Galván, 2000, Smc 2000 conference proceedings. 2000 ieee international conference on systems, man and cybernetics. 'cybernetics evolving to systems, humans, organizations, and their complex interactions' (cat. no.0.

Machine learning techniques for daily solar energy prediction and interpolation using numerical weather models

Inés María Galván, R. Martin, José María Valls, 2016, Concurr. Comput. Pract. Exp..

Deferring the Learning for Better Generalization in Radial Basis Neural Networks

Inés María Galván, José María Valls, Pedro Isasi Viñuela, 2001, ICANN.

AMPSO: A New Particle Swarm Method for Nearest Neighborhood Classification

Inés María Galván, Pedro Isasi Viñuela, Alejandro Cervantes, 2009, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

Discriminant Regression Analysis to Find Homogeneous Structures

Inés María Galván, Esteban García-Cuesta, Antonio J. de Castro, 2009, IDEAL.

Time-stamped resampling for robust evolutionary portfolio optimization

Inés María Galván, Pedro Isasi Viñuela, Sandra García-Rodríguez, 2012, Expert Syst. Appl..

Improving the Generalization Ability of RBNN Using a Selective Strategy Based on the Gaussian Kernel Function

Inés María Galván, José María Valls, Pedro Isasi Viñuela, 2006, Comput. Artif. Intell..

Michigan Particle Swarm Optimization for Prototype Reduction in Classification Problems

Inés María Galván, Pedro Isasi Viñuela, Alejandro Cervantes, 2008, New Generation Computing.

A filter attribute selection method based on local reliable information

Inés María Galván, Ricardo Aler, Ricardo Martín, 2017, Applied Intelligence.

Optimizing the Number of Learning Cycles in the Design of Radial Basis Neural Networks Using a Multi-Agent System

José M. Molina López, Inés María Galván, José María Valls, 2001, Comput. Artif. Intell..

Using Evolutionary Multiobjective Techniques for Imbalanced Classification Data

Inés María Galván, Ricardo Aler, Sandra García-Rodríguez, 2010, ICANN.

A Lazy Approach for Machine Learning Algorithms

Inés María Galván, José María Valls, Pedro Isasi Viñuela, 2009, AIAI.

Applying evolution strategies to preprocessing EEG signals for brain-computer interfaces

Inés María Galván, José María Valls, Ricardo Aler, 2012, Inf. Sci..

Extended mean-variance model for reliable evolutionary portfolio optimization

Inés María Galván, Pedro Isasi Viñuela, Sandra García-Rodríguez, 2014, AI Commun..

Improving Inverse Control on Real Time by Means of Neural Networks

Inés María Galván, D. Barrios, P. Jsasi, 1997, ICONIP.

A Study of Machine Learning Techniques for Daily Solar Energy Forecasting Using Numerical Weather Models

Inés María Galván, José María Valls, Ricardo Aler, 2014, IDC.

Evolving spatial and frequency selection filters for Brain-Computer Interfaces

Inés María Galván, José María Valls, Ricardo Aler, 2010, IEEE Congress on Evolutionary Computation.

Building Nearest Prototype Classifiers Using a Michigan Approach PSO

Inés María Galván, Pedro Isasi Viñuela, Alejandro Cervantes, 2007, 2007 IEEE Swarm Intelligence Symposium.

A First Attempt at Constructing Genetic Programming Expressions for EEG Classification

Inés María Galván, José María Valls, Ricardo Aler, 2005, ICANN.

Multilayer perceptron as inverse model in a ground-based remote sensing temperature retrieval problem

Inés María Galván, Esteban García-Cuesta, Antonio J. de Castro, 2008, Eng. Appl. Artif. Intell..

Multi-objective evolutionary optimization of prediction intervals for solar energy forecasting with neural networks

Inés María Galván, José María Valls, Ricardo Aler, 2017, Inf. Sci..

Wind Energy Forecasting at Different Time Horizons with Individual and Global Models

Inés María Galván, Ricardo Aler, Rubén Martín-Vázquez, 2018, AIAI.

An Adaptive Michigan Approach PSO for Nearest Prototype Classification

Inés María Galván, Pedro Isasi Viñuela, Alejandro Cervantes, 2007, IWINAC.

Learning radial basis neural networks in a lazy way: A comparative study

Inés María Galván, José María Valls, Pedro Isasi Viñuela, 2008, Neurocomputing.

A Selective Learning Method to Improve the Generalization of Multilayer Feedforward Neural Networks

Inés María Galván, José María Valls, Pedro Isasi Viñuela, 2001, Int. J. Neural Syst..

Studying the Effect of Measured Solar Power on Evolutionary Multi-objective Prediction Intervals

Inés María Galván, Ricardo Aler, Rubén Martín-Vázquez, 2018, IDEAL.

Multi-step Learning Rule for Recurrent Neural Models: An Application to Time Series Forecasting

Inés María Galván, Pedro Isasi Viñuela, 2004, Neural Processing Letters.

Multiobjective Algorithms with Resampling for Portfolio Optimization

Inés María Galván, Pedro Isasi Viñuela, Sandra García-Rodríguez, 2014, Comput. Informatics.

Optimizing the DFCN Broadcast Protocol with a Parallel Cooperative Strategy of Multi-Objective Evolutionary Algorithms

Francisco Luna, Gara Miranda, Eduardo Segredo, 2009, EMO.

Sistema Multiagente para el diseño de Redes de Neuronas de Base Radial Óptimas

José M. Molina López, Inés María Galván, José María Valls, 2000, Inteligencia Artif..

Recursive Discriminant Regression Analysis to Find Homogeneous Groups

Inés María Galván, Esteban García-Cuesta, Antonio J. de Castro, 2011, Int. J. Neural Syst..

A lazy learning approach for building classification models

Inés María Galván, José María Valls, Pedro Isasi Viñuela, 2011, Int. J. Intell. Syst..

Supervised clustering via principal component analysis in a retrieval application

Inés María Galván, Esteban García-Cuesta, Antonio J. de Castro, 2009, SensorKDD '09.

LRBNN: A Lazy Radial Basis Neural Network model

Inés María Galván, José María Valls, Pedro Isasi Viñuela, 2007, AI Commun..

Spectral High Resolution Feature Selection for Retrieval of Combustion Temperature Profiles

Inés María Galván, Esteban García-Cuesta, Antonio J. de Castro, 2006, IDEAL.

How the Selection of Training Patterns can Improve the Generalization Capability in Radial Basis Neural Networks

Inés María Galván, José María Valls, Pedro Isasi Viñuela, 2003, Applied Informatics.

A comparison between the Pittsburgh and Michigan approaches for the binary PSO algorithm

Inés María Galván, Pedro Isasi Viñuela, Alejandro Cervantes, 2005, 2005 IEEE Congress on Evolutionary Computation.

Non-Direct Encoding Method Based on Cellular Automata to Design Neural Network Architectures

Araceli Sanchis, José M. Molina López, Germán Gutiérrez, 2005, Comput. Artif. Intell..

Evolutionary Cellular Configurations for Designing Feed-Forward Neural Networks Architectures

Araceli Sanchis, José M. Molina López, Germán Gutiérrez, 2001, IWANN.

Lazy Learning in Radial Basis Neural Networks: A Way of Achieving More Accurate Models

Inés María Galván, José María Valls, Pedro Isasi Viñuela, 2004, Neural Processing Letters.

A Study on Feature Selection Methods for Wind Energy Prediction

Inés María Galván, Ricardo Aler, Rubén Martín-Vázquez, 2017, IWANN.

Improving Classification for Brain Computer Interfaces using Transitions and a Moving Window

Inés María Galván, José María Valls, Ricardo Aler, 2009, BIOSIGNALS.

Transition Detection for Brain Computer Interface Classification

Inés María Galván, José María Valls, Ricardo Aler, 2009, BIOSTEC.

A Better Selection of Patterns in Lazy Learning Radial Basis Neural Networks

Inés María Galván, José María Valls, Pedro Isasi Viñuela, 2003, IWANN.

Optimizing the number of electrodes and spatial filters for Brain-Computer Interfaces by means of an evolutionary multi-objective approach

Inés María Galván, Ricardo Aler, 2015, Expert Syst. Appl..

Multiobjective Algorithms Hybridization to Optimize Broadcasting Parameters in Mobile Ad-Hoc Networks

Inés María Galván, Alejandro Cervantes, Sandra García-Rodríguez, 2009, IWANN.

Predicting Global Irradiance Combining Forecasting Models Through Machine Learning

Inés María Galván, Ricardo Aler, J. Huertas-Tato, 2018, HAIS.

Evolutionary-based prediction interval estimation by blending solar radiation forecasting models using meteorological weather types

Inés María Galván, Ricardo Aler, David Pozo-Vázquez, 2021, Appl. Soft Comput..