Fuzzy Description Logics (DLs) are a formalism for the representation of structured knowledge that is imprecise or vague by nature. In fuzzy DLs, restricting to a finite set of degrees of truth has proved to be useful, both for theoretical and practical reasons. In this paper, we propose finite fuzzy DLs as a generalization of existing approaches. We assume a finite totally ordered set of lingu...

Fuzzy Description Logics (DLs) are a formalism for the representation of structured knowledge affected by imprecision or vagueness. In the setting of fuzzy DLs, restricting to a finite set of degrees of truth has proved to be useful. In this paper, we propose finite fuzzy DLs as a generalization of existing approaches. We assume a finite totally ordered set of linguistic terms or labels, which ...

When it is question of prediction, no deterministic model can be totally efficient, especially when the output to be estimated is dependent imprecisely on many fluctuant variables measuring human behavior (cognitions, choices, consumption, etc.). Regressions based on fuzzy logic which combine statistics and expert’s attitudes can be used to improve the estimation of such outputs. Those regressi...

We formalize reasoning about fuzzy belief and fuzzy common belief, especially incomparable beliefs, in multi-agent systems by using a logical system based on Fitting’s many-valued modal logic, where incomparable beliefs mean beliefs whose degrees are not totally ordered. Completeness and decidability results for the logic of fuzzy belief and common belief are established while implicitly exploi...

We consider a totally nonsymplectic (TNS) Anosov action of Zk which is either uniformly quasiconformal or pinched on each coarse Lyapunov distribution. We show that such an action on a torus is C∞–conjugate to an action by affine automorphisms. We also obtain similar global rigidity results for actions on an arbitrary compact manifold assuming that the coarse Lyapunov foliations are topological...

In this paper, an improved version of Principal Component Analysis (PCA) and Independent Component Analysis (ICA) is proposed for feature extraction to classify the ischemic beats from electrocardiogram (ECG) signal. The Fuzzy C-Means (FCM) and Genetic Algorithm (GA) is combined with PCA and ICA to extract more relevant features; the proposed methods are named as Fuzzy-Genetic based PCA (FGPCA)...

A fuzzy-genetic data-mining algorithm for extracting both association rules and membership functions from quantitative transactions is shown in this paper. It used a combination of large 1-itemsets and membershipfunction suitability to evaluate the fitness values of chromosomes. The calculation for large 1itemsets could take a lot of time, especially when the database to be scanned could not to...

Fuzzy economic models to evaluate the economic feasibility of information security investment for decision-makers is derived in this study. The Net Present Value and discounted Return on Investment models are proposed for the execution of cost-benefit analysis. Fuzzy mathematics is based on the extended principles which ensured that the resultant fuzzy number continuously maintained its fuzzy p...

MOLGEN 5.x combines the efficiency of the molecular generator MOLGEN 3.5 and the flexibility of MOLGEN 4.x . To achieve this, the software was reimplemented based on a totally new concept. The most visible new features are fuzzy molecular formula input and explicit use of atom state patterns. We describe the version MOLGEN 5.0 of this new series.

We introduce two frameworks for constraint solving where classical CSPs, fuzzy CSPs, weighted CSPs, partial constraint satisfaction , and others can be easily cast. One is based on a semiring, and the other one on a totally ordered commutative monoid. We then compare the two approaches and we discuss the relationship between them.