Publicaciones
] A Baseline Learning Genetic Fuzzy Classifier Based on Low Quality Data.,
, 01, p.803-808, (2009)
A fuzzy definition of mutual information with application to the design of genetic fuzzy classifiers,
, International Conference on Machine Intelligencea: ACIDCA-ICMI , 01, Tunez, (2005)
A Minimum Risk Wrapper Algorithm for Genetically Selecting Imprecisely Observed Features, Applied to the Early Diagnosis of Dyslexia,
, Lecture Notes in Computer Science - LNCS, 09, Volume 5271, p.608-615, (2008)
A Minimum-Risk Genetic Fuzzy Classifier Based on Low Quality Data,
, Hybrid Artificial Intelligence Systems, Berlin, Heidelberg, p.654–661, (2009)
Defuzzification of Fuzzy p-Values,
, Soft Methods for Handling Variability and Imprecision, Berlin, Heidelberg, p.126–132, (2008)
Generalized stochastic orderings applied to the study of perfomance of machine learning algorithm,
, The 16th World Congress of the International Fuzzy Systems Association (IFSA) and the 9th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT), 06, Gijón, Asturias(Spain), (2015)
GFS-Based Analysis of Vague Databases in High Performance Athletics,
, 09, p.602-609, (2009)
Managing imprecisely observed data in Genetic Fuzzy Models by means of a fuzzy-valued fitness function,
, Congreso español de metaheurísticas, algoritmos evolutivos y bioinspirados., 01, Granada (España), (2005)
Managing stochastic algorithms cross-validation variability using an interval valued multiple comparison procedure,
, International Conference on Intelligent Systems Design and Applications, 11, p.1391-1396, (2011)
Online SOC estimation of Li-FePO4 batteries through an observer of the system state with minimal nonspecificity,
, 08, p.1-8, (2015)
Selecting the Most Informative Inputs in Modelling Problems with Vague Data Applied to the Search of Informative Code Metrics for Continuous Assessment in Computer Science Online Courses,
, Rough Sets and Current Trends in Computing, Cham, p.299–308, (2014)
A methodology for exploiting the tolerance for imprecision in genetic fuzzy systems and its application to characterization of rotorblade leading edge materials,
, Mechanical Systems and Signal Processing, 06, Volume 37, p.76-91, (2013)
COMBINING ADABOOST WITH PREPROCESSING ALGORITHMS FOR EXTRACTING FUZZY RULES FROM LOW QUALITY DATA IN POSSIBLY IMBALANCED PROBLEMS,
, International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, Volume 20, Number supp02, p.51-71, (2012)
Extending a simple genetic cooperative-competitive learning fuzzy classifier to low quality datasets,
, Evolutionary Intelligence, 11, Volume 2, p.73-84, (2009)
Future Performance Modeling in Athletism with Low Quality Data-based Genetic Fuzzy Systems,
, Multiple-Valued Logic and Soft Computing, 01, Volume 17, p.207-228, (2011)
Interval-valued Blind Source Separation Applied to AI-based Prognostic Fault Detection of Aircraft Engines,
, Journal of Multiple-Valued Logic and Soft Computing, 01, Volume 22, p.151-166, (2014)
Learning from imprecise examples with GA-P algorithms,
, Mathware & soft computing, ISSN 1134-5632, Vol. 5, Nº. 2-3, 1998, pags. 305-319, 01, Volume 5, (1998)
Obtaining fuzzy rules from interval-censored data with genetic algorithms and a random sets-based semantic of the linguistic labels,
, Soft Comput., 10, Volume 15, p.1945-1957, (2011)
Obtaining linguistic fuzzy rule-based regression models from imprecise data with multiobjective genetic algorithms,
, Soft Comput., 03, Volume 13, p.467-479, (2009)
Singular spectral analysis of ill-known signals and its application to predictive maintenance of windmills with SCADA records,
, Soft Computing, 05, Volume 16, (2011)
Using fuzzy preference orderings in theta-dominance with application to health monitoring of Li-ion batteries,
, Journal of Multiple-Valued Logic and Soft Computing, (2017)