A method for response integration in modular neural networks with type-2 fuzzy logic for biometric systems p. 5 Evolving type-2 fuzzy logic controllers for autonomous mobile robots p. 16 Adaptive type-2 fuzzy logic for intelligent home environment p. 26 Interval type-1 non-singleton type-2 TSK fuzzy logic systems using the hybrid training method RLS-BP p. 36 An efficient computational method to...

A preference matrix is the result of pairwise comparison and is a powerful method in multi-criteria optimization. When comparing two elements, the decision maker assigns the value from a given scale which is a linearly ordered Abelian group (Alogroup) to any pair of alternatives representing the element of the preference matrix (P-matrix). The well known multiplicative, additive and fuzzy prefe...

Gradual patterns refer to frequent patterns describing correlations between variables which evolution is linked. For instance, the gradual pattern the older, the higher the salary means that the age and the salary increase/decrease simultaneously between two persons. This co-evolution can be found either as increasing together or evolving oppositely (e.g., the more cars, the less bus tickets). ...

In this paper, we take a GL-quantale as the truth value table to study a new rough set model—L-valued fuzzy rough sets. The three key components of this model are: an L-fuzzy set A as the universal set, an L-valued relation of A and an L-fuzzy set of A (a fuzzy subset of fuzzy sets). Then L-valued fuzzy rough sets are completely characterized via both constructive and axiomatic approaches. 

In this paper we rst summarize t he more important aspects of a Logic Fuzzy Relational Database and w e s h ow h ow a fuzzy relational database can be representedand h andled using rst order logic. Given that t he results obtained for fuzzy databasesare satisfactory, we are tackling now t he problem of uncertain fuzzy databases considering that t he fuzzy values stored in the d a tabase are att...

In many real life problems, the parameters used to characterize the uncertainty or vagueness or impreciseness in information are either triangular or trapezoidal fuzzy numbers. But it is not always possible to restrict the membership function to either triangular or trapezoidal form. In this paper, a new form of non-normal fuzzy number named as Heptagonal fuzzy number is introduced and its arit...

Fuzzy numbers, and more generally linguistic values, are approximate assessments, given by experts and accepted by decision-makers when obtaining more accurate values is impossible or unnecessary. To simplify the task of representing and handling fuzzy numbers, several authors have introduced real indices in order to capture the information contained in a fuzzy number. In this paper we propose ...

In this paper we investigated the correlation between two fuzzy sets de ned on the same universal support. It is shown that Spearman’s rank correlation coe cient can be applied if the members of the supports are ranked according to the fuzzy membership values of each set. Next a membership-value-based fuzzy correlation measure is proposed and its properties are explained. The proposed measure i...

Fuzzy logic due to its nature of characterizing each case with multiple values offers is a rich field of resources covering the assessment of situations characterized by a degree of fuzziness and/or uncertainty. In this paper, we present two different fuzzy assessment models: The Centre of Gravity (COG) model and Trapezoidal Fuzzy Assessment Model (TRFAM). The last one is a new model covering t...