In many domains of information processing, both vagueness, or imprecision, and bipolarity, encompassing positive and negative parts of information, are core features of the information to be modeled and processed. This led to the development of the concept of bipolar fuzzy sets, and of associated models and tools. Here we propose to extend these tools by defining algebraic relations between bip...

The aim of this paper is to build a formal model for similarity-based fuzzy unification in multi-adjoint logic programs. Specifically, a general framework of logic programming which allows the simultaneous use of different implications in the rules and rather general connectives in the bodies is introduced, then a procedural semantics for this framework is presented, and an aproximative-complet...

Cooccurrence graphs easily grow very dense when applied to represent binary association patterns of large amounts of data. Therefore, postprocessing is needed to extract valuable information from them. We propose an approach to identify subgraphs of cooccurrence graphs that show a certain temporal behavior. This behavior is described with linguistic variables and fuzzy connectives defined over ...

Possibilistic states of information are fuzzy sets of possible worlds. They constitute a complete lattice, which can be endowed with a monoidal operation (a t-norm) to produce a quantal. An algebraic semantics is presented which links possibilistic formulae with information states, and gives a natural interpretation of logical connectives as operations on fuzzy sets. Due to the quantal structur...

Aggregation of information represented by membership functions is a central matter in intelligent systems where fuzzy rule base and reasoning mechanism are applied. Typical examples of such systems consist of, but not limited to, fuzzy control, decision support and expert systems. Since the advent of fuzzy sets a great number of fuzzy connectives, aggregation operators have been introduced. Som...

Most normal forms for fuzzy logics are versions of conjunctive and disjunctive classical normal forms. Unfortunately, they do not always preserve either tautologies or contradictions which are fundamental for automatic theorem provers based on refutation methods. De Morgan implicative systems are triples like the De Morgan system, but considering fuzzy implications instead of t-conorms. These s...

We design a fuzzy model of the loadings of 10 heavy metals in Liverpool bay. Each metal concentration is associated with a fuzzy set “contaminated”, defined over the set of 70 sampling sites. The higher the concentration, the higher the degree of membership of the site. Six overall loading indices are calculated using aggregation connectives between fuzzy sets. The loading indices are then inte...

In the last decades, more than a hundred families of fuzzy implication functions have been proposed. These are generated by adequately combining other logical connectives or univariate functions. However, no attention has given to final expression function, crucial feature for any application. this paper, polynomial implications introduced as those whose is two variables. Polynomials present ad...

In this paper we present interesting relationships between the context model, modal logic and fuzzy concept analysis. It has been shown that the context model proposed by Gebhardt and Kruse [Int. J. Approx. Reason. 9 (1993) 283] can be semantically extended and considered as a data model for fuzzy concept analysis within the framework of the meta-theory developed by Resconi et al. in 1990s. Con...

compositionality. At AAAI’93, Elkan has claimed to have a result trivializing fuzzy logic. This trivialization is based on too strong a view of equivalence in fuzzy logic and relates to a fully compositional treatment of uncertainty. Such a treatment is shown to be impossible in this paper. We emphasize the distinction between i) degrees of partial truth which are allowed to be truth functional...