A T-fuzzy equivalence relation is a fuzzy binary relation on a set X which is reflexive, symmetric and T-transitive for a t-norm T. Recently, Mesiar et al. [R. Mesiar, B. Reusch, H. Thiele, Fuzzy equivalence relations and fuzzy partitions, J. Multi-Valued Logic Soft Comput. 12 (2006) 167–181] have generalised the t-norm T to any general conjunctor C and investigated the minimal assumptions requ...

Your Texture analysis is one of the most important techniques used in the analysis and interpretation of images, consisting of repetition or quasi repetition of some fundamental image elements. The present paper derived Fuzzy Triangular Greylevel Pattern (FTGP) to overcome the disadvantages of LBP and other local approaches. The FTGP is a 2 x 2 matrix that is derived from a 3 x 3 neighborhood m...

Recent trends in field of wireless networks is setting up Wireless Sensor Networks that, senses specified parameter(s) related to environment; processes sensed data and wirelessly communicates it to a base station. Such networks open up a whole new range of applications, including precision agriculture, monitoring and tracking vehicles, animals and humans, battle-field surveillance, civil struc...

Recent trends in field of wireless networks is setting up Wireless Sensor Networks that, senses specified parameter(s) related to environment; processes sensed data and wirelessly communicates it to a base station. Such networks open up a whole new range of applications, including precision agriculture, monitoring and tracking vehicles, animals and humans, battle-field surveillance, civil struc...

Our special fuzzy classifier operates on the set of eight features extracted from the 3x3 neighborhood of each pixel. These features are the magnitudes of differences between that pixel and the eight neighboring pixels. They are input into the fuzzy classifier inputs that connect to two fuzzy set membership functions that represent “white background” or “black edge.” The paradigm is simple, com...

The paper deals in a preliminary way with the problem of the selection of a unique fuzzy preference relation from the set of fuzzy preference relations. A direct algorithm of possibilistic clustering is the basis of the method of fuzzy preference relation discriminating. A method of decision-making based on a fuzzy preference relation is described and basic concepts of the heuristic method of p...

This work focuses on adapting artificial intelligence techniques for urban growth modeling using multitemporal imagery. Fuzzy set theory and cellular automata are used for this purpose. Fuzzy set theory preserves the spatial continuity of the growth process through allowing a test pixel to be partially developed unlike the binary crisp system (developed/undeveloped). The development level ident...

There are fast known algorithms to compute the transitive closure of a fuzzy relation, but there are only a few different algorithms that compute T-transitive low approximations of a fuzzy relation. A fast method to compute a T-transitive low approximation of a reflexive and symmetric fuzzy relation is given for any continuous tnorm, spending O(n) time.

We introduce and study the construction of commutative fundamental relation in fuzzy hypersemigroups and investigate its basic properties. We will determine some necessary and sufficient conditions so that this relation is transitive in fuzzy hypersemigroups. Also we show that this relation is transitive in every fuzzy hypergroup.