Important advances have been made in the fuzzy quantification field. Nevertheless, some problems remain when we face the decision of selecting the most convenient model for a specific application. In the literature, several desirable adequacy properties have been proposed, but theoretical limits impede quantification models from simultaneously fulfilling every adequacy property that has been de...

In this paper we present how to extract fuzzy association rules involving both the presence and the absence of items using a fuzzy rule mining procedure introduced by the authors in previous works. The rule mining procedure is based on the GUHA logical model, fuzzified via a recently proposed representation of gradualness. We present some results obtained with real datasets.

Established simulation techniques require quantification of relevant aspects of the entity whose behaviour is being investigated. The data expressing the quantification provides a disciplined link between the simulation model and the domain being modelled. In this connection, domains such as software projects or processes that are, for example, fuzzy, uncertain or lack precise data quantificati...

The aim of this paper is to give a. sketch of a foundation of statistical analysis with fuzzy data, extending the methodology of Mathematical Stat,istics. For t.his purpose it will be discussed to equip the fuzzy sample spaces with suitable a-algebras and metrics. As the main application the parameter estimation in linear regression models with crisp parameters und fuzzy-valued variables will b...

Up to now, several approaches have been proposed for ranking of fuzzy numbers using maximizing set and minimizing sets. Often, the reference points are created by real numbers. In this paper, we proposed new reference points so called fuzzy maximizing-minimizing points. To this purpose, we used the center of gravity of fuzzy numbers and their left/right spreads to construct such fuzzy points. M...

The management of uncertainty and imprecision is becoming more and more important in knowledge-based systems. Fuzzy logic provides a systematic basis for representing and inferring with this kind of knowledge. This paper describes an approach for fuzzy inference based on an uncertainty forward propagation method and a change in the granularity of the elements involved. The proposed model is abl...

In recent years, adaptive learning systems rely increasingly on learning hierarchy to customize the educational logic developed in their courses. Most approaches do not consider that the relationships of prerequisites between the skills are fuzzy relationships. In this article, we describe a new approach of a practical application of fuzzy logic techniques to the construction of learning hierar...

We consider the aggregation operators which are ⊕-additive for commonotone functions. The main result is that any operator is expressed by a kind of general fuzzy integral which uses a family of fuzzy measures connected by a ⊕-additive Cauchy’s equations. In particular, the family of fuzzy measures can be obtained by a ⊕-fitting pseudomultiplication. In this case, the aggregation operator is ex...

Based on fuzzy set theory, flexible querying enables users to express preferences inside requirements. Quantifications and preferences on data have led us to define the notion of fuzzy integers ( f). This framework has been extended (to f and f ) in order to dealing with queries based on difference or division operations. In this paper we study how to define fuzzy order relations between such f...

Firstly, soft hyperideals of hyperlattices are introduced and several interesting examples of them are given. Secondly, fuzzy soft hyperideals are proposed, which are generalizations of hyperideals and soft hyperideals in hyperlattices. After that, equivalent conditions of fuzzy soft hyperideals are given by using level soft sets. Finally, under the fuzzy soft homomorphism of hyperlattices, the...