@article {551,
	title = {Using fuzzy preference orderings in theta-dominance with application to health monitoring of Li-ion batteries},
	journal = {Journal of Multiple-Valued Logic and Soft Computing},
	year = {2017},
	author = {Echevarr{\'\i}a, Yuviny and Couso, In{\'e}s and Anse{\'a}n, David and Blanco, Cecilio and S{\'a}nchez, Luciano}
}
@conference {654,
	title = {Generalized stochastic orderings applied to the study of perfomance of  machine learning algorithm},
	booktitle = {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)},
	year = {2015},
	month = {06},
	address = {Gij{\'o}n, Asturias(Spain)},
	author = {Couso, In{\'e}s and S{\'a}nchez, Luciano}
}
@conference {inproceedings,
	title = {Online SOC estimation of Li-FePO4 batteries through an observer of the system state with minimal nonspecificity},
	year = {2015},
	month = {08},
	pages = {1-8},
	doi = {10.1109/FUZZ-IEEE.2015.7337901},
	author = {S{\'a}nchez, Luciano and Couso, In{\'e}s and Blanco, Cecilio}
}
@article {article,
	title = {Interval-valued Blind Source Separation Applied to AI-based Prognostic Fault Detection of Aircraft Engines},
	journal = {Journal of Multiple-Valued Logic and Soft Computing},
	volume = {22},
	year = {2014},
	month = {01},
	pages = {151-166},
	author = {Martinez, Alvaro and S{\'a}nchez, Luciano and Couso, In{\'e}s}
}
@conference {10.1007/978-3-319-08644-6_31,
	title = {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},
	booktitle = {Rough Sets and Current Trends in Computing},
	year = {2014},
	pages = {299{\textendash}308},
	publisher = {Springer International Publishing},
	organization = {Springer International Publishing},
	address = {Cham},
	abstract = {Sorting a set of inputs for relevance in modeling problems may be ambiguous if the data is vague. A general extension procedure is proposed in this paper that allows applying different deterministic or random feature selection algorithms to fuzzy data. This extension is based on a model of the relevance of a feature as a possibility distribution. The possibilistic relevances are ordered with the help of a fuzzy ranking. A practical problem where the most informative software metrics are searched for in an automatic grading problem is solved with this technique.},
	isbn = {978-3-319-08644-6},
	author = {Otero, Jos{\'e} and Del Rosario Su{\'a}rez, Maria and Palacios, Ana and Couso, In{\'e}s and S{\'a}nchez, Luciano},
	editor = {Cornelis, Chris and Kryszkiewicz, Marzena and {\'S}lȩzak, Dominik and Ruiz, Ernestina Menasalvas and Bello, Rafael and Shang, Lin}
}
@article {article,
	title = {A methodology for exploiting the tolerance for imprecision in genetic fuzzy systems and its application to characterization of rotorblade leading edge materials},
	journal = {Mechanical Systems and Signal Processing},
	volume = {37},
	year = {2013},
	month = {06},
	pages = {76-91},
	doi = {10.1016/j.ymssp.2012.02.009},
	author = {S{\'a}nchez, Luciano and Couso, In{\'e}s and Palacios, Ana and Palacios, Jos{\'e}}
}
@article {doi:10.1142/S0218488512400156,
	title = {COMBINING ADABOOST WITH PREPROCESSING ALGORITHMS FOR EXTRACTING FUZZY RULES FROM LOW QUALITY DATA IN POSSIBLY IMBALANCED PROBLEMS},
	journal = {International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems},
	volume = {20},
	number = {supp02},
	year = {2012},
	pages = {51-71},
	abstract = {An extension of the Adaboost algorithm for obtaining fuzzy rule-based systems from low quality data is combined with preprocessing algorithms for equalizing imbalanced datasets. With the help of synthetic and real-world problems, it is shown that the performance of the Adaboost algorithm is degraded in presence of a moderate uncertainty in either the input or the output values. It is also established that a preprocessing stage improves the accuracy of the classifier in a wide range of binary classification problems, including those whose imbalance ratio is uncertain.},
	doi = {10.1142/S0218488512400156},
	url = {https://doi.org/10.1142/S0218488512400156},
	author = {Palacios, Ana and S{\'a}nchez, Luciano and Couso, In{\'e}s}
}
@article {article,
	title = {Future Performance Modeling in Athletism with Low Quality Data-based Genetic Fuzzy Systems},
	journal = {Multiple-Valued Logic and Soft Computing},
	volume = {17},
	year = {2011},
	month = {01},
	pages = {207-228},
	author = {Palacios, Ana and S{\'a}nchez, Luciano and Couso, In{\'e}s}
}
@conference {inproceedings,
	title = {Managing stochastic algorithms cross-validation variability using an interval valued multiple comparison procedure},
	booktitle = {International Conference on Intelligent Systems Design and Applications},
	year = {2011},
	month = {11},
	pages = {1391-1396},
	doi = {10.1109/ISDA.2011.6121854},
	author = {Otero, Jos{\'e} and S{\'a}nchez, Luciano and Palacios, Ana and Couso, In{\'e}s}
}
@article {article,
	title = {Obtaining fuzzy rules from interval-censored data with genetic algorithms and a random sets-based semantic of the linguistic labels},
	journal = {Soft Comput.},
	volume = {15},
	year = {2011},
	month = {10},
	pages = {1945-1957},
	doi = {10.1007/s00500-010-0627-6},
	author = {S{\'a}nchez, Luciano and Couso, In{\'e}s}
}
@article {article,
	title = {Singular spectral analysis of ill-known signals and its application to predictive maintenance of windmills with SCADA records},
	journal = {Soft Computing},
	volume = {16},
	year = {2011},
	month = {05},
	doi = {10.1007/s00500-011-0767-3},
	author = {S{\'a}nchez, Luciano and Couso, In{\'e}s}
}
@conference {inproceedings,
	title = {A Baseline Learning Genetic Fuzzy Classifier Based on Low Quality Data.},
	year = {2009},
	month = {01},
	pages = {803-808},
	author = {Palacios, Ana and S{\'a}nchez, Luciano and Couso, In{\'e}s}
}
@conference {10.1007/978-3-642-02319-4_79,
	title = {A Minimum-Risk Genetic Fuzzy Classifier Based on Low Quality Data},
	booktitle = {Hybrid Artificial Intelligence Systems},
	year = {2009},
	pages = {654{\textendash}661},
	publisher = {Springer Berlin Heidelberg},
	organization = {Springer Berlin Heidelberg},
	address = {Berlin, Heidelberg},
	abstract = {Minimum risk classification problems use a matrix of weights for defining the cost of misclassifying an object. In this paper we extend a simple genetic fuzzy system (GFS) to this case. In addition, our method is able to learn minimum risk fuzzy rules from low quality data. We include a comprehensive description of the new algorithm and discuss some issues about its fuzzy-valued fitness function. A synthetic problem, plus two real-world datasets, are used to evaluate our proposal.},
	isbn = {978-3-642-02319-4},
	author = {Palacios, Ana M. and S{\'a}nchez, Luciano and Couso, In{\'e}s},
	editor = {Corchado, Emilio and Wu, Xindong and Oja, Erkki and Herrero, {\'A}lvaro and Baruque, Bruno}
}
@article {article,
	title = {Extending a simple genetic cooperative-competitive learning fuzzy classifier to low quality datasets},
	journal = {Evolutionary Intelligence},
	volume = {2},
	year = {2009},
	month = {11},
	pages = {73-84},
	doi = {10.1007/s12065-009-0024-1},
	author = {Palacios, Ana and S{\'a}nchez, Luciano and Couso, In{\'e}s}
}
@conference {inproceedings,
	title = {GFS-Based Analysis of Vague Databases in High Performance Athletics},
	year = {2009},
	month = {09},
	pages = {602-609},
	doi = {10.1007/978-3-642-04394-9_73},
	author = {Palacios, Ana and Couso, In{\'e}s and S{\'a}nchez, Luciano}
}
@article {article,
	title = {Obtaining linguistic fuzzy rule-based regression models from imprecise data with multiobjective genetic algorithms},
	journal = {Soft Comput.},
	volume = {13},
	year = {2009},
	month = {03},
	pages = {467-479},
	doi = {10.1007/s00500-008-0362-4},
	author = {S{\'a}nchez, Luciano and Otero, Jos{\'e} and Couso, In{\'e}s}
}
@conference {inproceedings,
	title = {A Minimum Risk Wrapper Algorithm for Genetically Selecting Imprecisely Observed Features, Applied to the Early Diagnosis of Dyslexia},
	booktitle = {Lecture Notes in Computer Science - LNCS},
	volume = {5271},
	year = {2008},
	month = {09},
	pages = {608-615},
	doi = {10.1007/978-3-540-87656-4_75},
	author = {S{\'a}nchez, Luciano and Palacios, Ana and Couso, In{\'e}s}
}
@conference {10.1007/978-3-540-85027-4_16,
	title = {Defuzzification of Fuzzy p-Values},
	booktitle = {Soft Methods for Handling Variability and Imprecision},
	year = {2008},
	pages = {126{\textendash}132},
	publisher = {Springer Berlin Heidelberg},
	organization = {Springer Berlin Heidelberg},
	address = {Berlin, Heidelberg},
	abstract = {We provide a new description of the notion of fuzzy p-value, within the context of the theory of imprecise probabilities. The fuzzy p-value is viewed as a representation of a certain second-order possibility measure. According to Walley, any second-order possibility measure can be converted into a pair of lower and upper probabilities. Thus, we can convert the fuzzy p-value into an interval in the real line. We derive a construction of imprecise (but non fuzzy) tests, which are formally similar to recent tests used to manage with set-valued data.},
	isbn = {978-3-540-85027-4},
	author = {Couso, In{\'e}s and S{\'a}nchez, Luciano},
	editor = {Dubois, Didier and Lubiano, M. Asunci{\'o}n and Prade, Henri and Gil, Mar{\'\i}a {\'A}ngeles and Grzegorzewski, Przemys{\l}aw and Hryniewicz, Olgierd}
}
@conference {article,
	title = {A fuzzy definition of mutual information with application to the design of genetic fuzzy classifiers},
	booktitle = {International Conference on Machine Intelligencea: ACIDCA-ICMI },
	year = {2005},
	month = {01},
	address = {Tunez},
	author = {S{\'a}nchez, Luciano and Su{\'a}rez, Mar{\'\i}a and Couso, In{\'e}s}
}
@conference {article,
	title = {Managing imprecisely observed data in Genetic Fuzzy Models by means of a fuzzy-valued fitness function},
	booktitle = {Congreso espa{\~n}ol de metaheur{\'\i}sticas, algoritmos evolutivos y bioinspirados.},
	year = {2005},
	month = {01},
	address = {Granada (Espa{\~n}a)},
	author = {S{\'a}nchez, Luciano and Couso, In{\'e}s}
}
@article {article,
	title = {Learning from imprecise examples with GA-P algorithms},
	journal = {Mathware \& soft computing, ISSN 1134-5632, Vol. 5, N{\textordmasculine}. 2-3, 1998, pags. 305-319},
	volume = {5},
	year = {1998},
	month = {01},
	author = {S{\'a}nchez, Luciano and Couso, In{\'e}s}
}
