# Person: Bustince Sola, Humberto

Loading...

## Email Address

## Birth Date

## Research Projects

## Organizational Units

## Job Title

## Last Name

Bustince Sola

## First Name

Humberto

## person.page.departamento

Automática y Computación

## ORCID

0000-0002-1279-6195

## person.page.upna

278

## Name

181 results Back to results

### Filters

#### Author

#### Date

#### Has files

#### Item Type

### Settings

Sort By

Results per page

## Search Results

Now showing 1 - 10 of 181

Publication Open Access Linking mathematical morphology and L-fuzzy concepts(World Scientific, 2017) Alcalde, Cristina; Burusco Juandeaburre, Ana; Bustince Sola, Humberto; Fuentes González, Ramón; Sesma Sara, Mikel; Automatika eta Konputazioa; Institute of Smart Cities - ISC; Automática y ComputaciónShow more In this paper we study the relation between L-fuzzy morphology and L-fuzzy concepts over complete lattices. In particular, we show how the erosion and dilation operators of the former can be understood in terms of the derivation operators of the latter, even when the set of objects is different from the set of attributes.Show more Publication Open Access Improving the performance of fuzzy rule-based classification systems with interval-valued fuzzy sets and genetic amplitude tuning(Elsevier, 2010) Sanz Delgado, José Antonio; Fernández, Alberto; Bustince Sola, Humberto; Herrera, Francisco; Automática y Computación; Automatika eta KonputazioaShow more Among the computational intelligence techniques employed to solve classification problems, Fuzzy Rule-Based Classification Systems (FRBCSs) are a popular tool because of their interpretable models based on linguistic variables, which are easier to understand for the experts or end-users. The aim of this paper is to enhance the performance of FRBCSs by extending the Knowledge Base with the application of the concept of Interval-Valued Fuzzy Sets (IVFSs). We consider a post-processing genetic tuning step that adjusts the amplitude of the upper bound of the IVFS to contextualize the fuzzy partitions and to obtain a most accurate solution to the problem. We analyze the goodness of this approach using two basic and well-known fuzzy rule learning algorithms, the Chi et al.’s method and the fuzzy hybrid genetics-based machine learning algorithm. We show the improvement achieved by this model through an extensive empirical study with a large collection of data-sets.Show more Publication Open Access Paired structures in knowledge representation(Elsevier, 2016) Montero, Javier; Bustince Sola, Humberto; Pagola Barrio, Miguel; Fernández Fernández, Francisco Javier; Barrenechea Tartas, Edurne; Automática y Computación; Automatika eta KonputazioaShow more In this position paper we propose a consistent and unifying view to all those basic knowledge representation models that are based on the existence of two somehow opposite fuzzy concepts. A number of these basic models can be found in fuzzy logic and multi-valued logic literature. Here it is claimed that it is the semantic relationship between two paired concepts what determines the emergence of different types of neutrality, namely indeterminacy, ambivalence and conflict, widely used under different frameworks (possibly under different names). It will be shown the potential relevance of paired structures, generated from two paired concepts together with their associated neutrality, all of them to be modeled as fuzzy sets. In this way, paired structures can be viewed as a standard basic model from which different models arise. This unifying view should therefore allow a deeper analysis of the relationships between several existing knowledge representation formalisms, providing a basis from which more expressive models can be later developed.Show more Publication Open Access A survey on fingerprint minutiae-based local matching for verification and identification: taxonomy and experimental evaluation(Elsevier, 2015) Peralta, Daniel; Galar Idoate, Mikel; Triguero, Isaac; Paternain Dallo, Daniel; García, Salvador; Barrenechea Tartas, Edurne; Benítez, José Manuel; Bustince Sola, Humberto; Herrera, Francisco; Automática y Computación; Automatika eta KonputazioaShow more Fingerprint recognition has found a reliable application for verification or identification of people in biometrics. Globally, fingerprints can be viewed as valuable traits due to several perceptions observed by the experts; such as the distinctiveness and the permanence on humans and the performance in real applications. Among the main stages of fingerprint recognition, the automated matching phase has received much attention from the early years up to nowadays. This paper is devoted to review and categorize the vast number of fingerprint matching methods proposed in the specialized literature. In particular, we focus on local minutiae-based matching algorithms, which provide good performance with an excellent trade-off between efficacy and efficiency. We identify the main properties and differences of existing methods. Then, we include an experimental evaluation involving the most representative local minutiae-based matching models in both verification and evaluation tasks. The results obtained will be discussed in detail, supporting the description of future directions.Show more Publication Open Access Extension of restricted equivalence functions and similarity measures for type-2 fuzzy sets(IEEE, 2021) Miguel Turullols, Laura de; Santiago, Regivan; Wagner, Christian; Garibaldi, Jonathan M.; Takáč, Zdenko; Roldán López de Hierro, Antonio Francisco; Bustince Sola, Humberto; Estatistika, Informatika eta Matematika; Institute of Smart Cities - ISC; Estadística, Informática y Matemáticas; Universidad Pública de Navarra / Nafarroako Unibertsitate PublikoaShow more In this work we generalize the notion of restricted equivalence function for type-2 fuzzy sets, leading to the notion of extended restricted equivalence functions. We also study how under suitable conditions, these new functions recover the standard axioms for restricted equivalence functions in the real setting. Extended restricted equivalence functions allow us to compare any two general type-2 fuzzy sets and to generate a similarity measure for type-2 fuzzy sets. The result of this similarity is a fuzzy set on the same referential set (i.e., domain) as the considered type-2 fuzzy set. The latter is crucial for applications such as explainable AI and decision making, as it enables an intuitive interpretation of the similarity within the domain-specific context of the fuzzy sets. We show how this measure can be used to compare type-2 fuzzy sets with different membership functions in such a way that the uncertainty linked to type-2 fuzzy sets is not lost. This is achieved by generating a fuzzy set rather than a single numerical value. Furthermore, we also show how to obtain a numerical value for discrete referential sets.Show more Publication Embargo Directional monotonicity of multidimensional fusion functions with respect to admissible orders(Elsevier, 2023) Sesma Sara, Mikel; Bustince Sola, Humberto; Mesiar, Radko; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika; Institute of Smart Cities - ISC; Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa, PJUPNA25-2022Show more The notion of directional monotonicity emerged as a relaxation of the monotonicity condition of aggregation functions. As the extension of aggregation functions to fuse more complex information than numeric data, directional monotonicity was extended to the framework of multidimensional data, with respect to the product order, which is a partial order. In this work, we present the notion of admissible order for multidimensional data and we define the concept of directional monotonicity for multidimensional fusion functions with respect to an admissible order. Moreover, we study the main properties of directionally monotone functions in this new context. We conclude that, while some of the properties are still valid (e.g. the set of directions of increasingness is still closed under convex combinations), some of the main ones no longer hold (e.g. there does not exist a finite set of directions that characterize standard monotonicity in terms of directional monotonicity).Show more Publication Open Access CFM-BD: a distributed rule induction algorithm for building compact fuzzy models in Big Data classification problems(IEEE, 2020) Elkano Ilintxeta, Mikel; Sanz Delgado, José Antonio; Barrenechea Tartas, Edurne; Bustince Sola, Humberto; Galar Idoate, Mikel; Estatistika, Informatika eta Matematika; Institute of Smart Cities - ISC; Estadística, Informática y MatemáticasShow more Interpretability has always been a major concern for fuzzy rule-based classifiers. The usage of human-readable models allows them to explain the reasoning behind their predictions and decisions. However, when it comes to Big Data classification problems, fuzzy rule based classifiers have not been able to maintain the good tradeoff between accuracy and interpretability that has characterized these techniques in non-Big-Data environments. The most accurate methods build models composed of a large number of rules and fuzzy sets that are too complex, while those approaches focusing on interpretability do not provide state-of-the-art discrimination capabilities. In this paper, we propose a new distributed learning algorithm named CFM-BD to construct accurate and compact fuzzy rule-based classification systems for Big Data. This method has been specifically designed from scratch for Big Data problems and does not adapt or extend any existing algorithm. The proposed learning process consists of three stages: Preprocessing based on the probability integral transform theorem; rule induction inspired by CHI-BD and Apriori algorithms; and rule selection by means of a global evolutionary optimization. We conducted a complete empirical study to test the performance of our approach in terms of accuracy, complexity, and runtime. The results obtained were compared and contrasted with four state-of-the-art fuzzy classifiers for Big Data (FBDT, FMDT, Chi-Spark-RS, and CHI-BD). According to this study, CFM-BD is able to provide competitive discrimination capabilities using significantly simpler models composed of a few rules of less than three antecedents, employing five linguistic labels for all variables.Show more Publication Embargo Construction methods of fuzzy implications on bounded posets(Elsevier, 2024) Wang, Mei; Zhang, Xiaohong; Bustince Sola, Humberto; Fernández Fernández, Francisco Javier; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika; Institute of Smart Cities - ISCShow more The fuzzy implication on bounded lattices was introduced by Palmeira et al., and the method of extending fuzzy implications on bounded lattices by using retraction was provided. However, we find that the extension of fuzzy implications on bounded lattices can also be realized through homomorphism. In order to get better results, we will continue to study this topic in this paper. In particular, we will focus on the construction methods of fuzzy implications on bounded posets. More precisely, we will give some construction methods of fuzzy implications via 0,1-homomorphism on bounded posets. Then we further study two special kinds of fuzzy implications, (Q,N)-implications and RQ-implications on bounded posets, where Q is a quasi-overlap function. Finally, we discuss the distributive laws and the importation laws of (Q,N)-implications and RQ-implications over a quasi-overlap function Q.Show more Publication Open Access The null space of fuzzy inclusion measures(IEEE, 2019) Couso, Inés; Bustince Sola, Humberto; Fernández Fernández, Francisco Javier; Sánchez, Luciano; Estatistika, Informatika eta Matematika; Institute of Smart Cities - ISC; Estadística, Informática y MatemáticasShow more Some formal relationships between the different axiomatic definitions of inclusion measure are analysed. In particular, the links between the different proposals about the null-space (the collection of pairs associated with a null degree of inclusion) are studied. Taking as starting point the well-known axiomatics of Kitainik and Sinha-Dougherty, we observe that other alternative proposals about the null-space are incompatible with both the null-space and the decomposition axioms of these authors. We also conclude that both the axiomatics of Kitainik and that of Sinha-Dougherty contain certain redundancies. Reduced equivalent lists of axioms are proposed.Show more Publication Open Access On admissible orders over closed subintervals of [0,1](Elsevier, 2020) Santana, Fagner; Bedregal, Benjamin; Viana, Petrucio; Bustince Sola, Humberto; Estatistika, Informatika eta Matematika; Institute of Smart Cities - ISC; Estadística, Informática y MatemáticasShow more In this paper, we make some considerations about admissible orders on the set of closed subintervals of the unit interval I[0,1], i.e. linear orders that refine the product order on intervals. We propose a new way to generate admissible orders on I[0,1] which is more general than those we find in the current literature. Also, we deal with the possibility of an admissible order on I[0,1] to be isomorphic to the usual order on [0,1]. We prove that some orders constructed by our method are not isomorphic to the usual one and we make some considerations about the following question: is there some admissible order on I[0,1] isomorphic to the usual order on [0,1]?Show more