This article concerns a connection of fuzzy logic and lattice theory. Namely, the fuzzy sets form a Heyting lattice with union and intersection of fuzzy sets as meet and join operations. The lattice of fuzzy sets is defined as the product of interval posets. As the final result, we have characterized the composition of fuzzy relations in terms of lattice theory and proved its associativity.

The paper deals with an extension of aggregation operators from the set of real numbers (or interval [0, 1]) to the set of fuzzy truth values (fuzzy sets in [0, 1]). We define so-called type-2 aggregation operator and show that an extension of ordinary aggregation operator by convolution is a type-2 aggregation operator. Finally we show that ordinary aggregation operator, as well as aggregation...

Real-world systems present a variety of challenges to the modeller, not least of which is the problem of uncertainty inherent in their operation. In this research, an Interval Type-2 Fuzzy model is applied to a real-world problem, the goal being to discover a suitable optimisation configuration to enable a search for an inventory plan using the model. To this end, a series of Simulated Annealin...

on account of the existence of uncertainty, dea occasionally faces the situation of imprecise data, especially when a set of dmus include missing data, ordinal data, interval data, stochastic data, or fuzzy data. therefore, how to evaluate the efficiency of a set of dmus in interval environments is a problem worth studying. in this paper, we discussed the new method for evaluation and ranking i...

This article concerns a connection of fuzzy logic and lattice theory. Namely, the fuzzy sets form a Heyting lattice with union and intersection of fuzzy sets as meet and join operations. The lattice of fuzzy sets is defined as the product of interval posets. As the final result, we have characterized the composition of fuzzy relations in terms of lattice theory and proved its associativity.

it is firstly proved that the multi-input-single-output (miso) fuzzy systems based on interval-valued $r$- and $s$-implications can approximate any continuous function defined on a compact set to arbitrary accuracy.  a formula to compute the lower upper bounds on the number  of interval-valued fuzzy sets needed to achieve a pre-specified approximation  accuracy for an arbitrary multivariate con...

In this paper, we present a type-2 fuzzy logic based system for robustly extracting the human silhouette which is a fundamental and important procedure for advanced video processing applications, such as pedestrian tracking, human activity analysis and event detection. The presented interval type-2 fuzzy logic system is able to detach moving objects from extracted human silhouette in dynamic en...