The concept of fuzzy sets and fuzzy set operations were first introduced by Zadeh [30], fuzzy logic has become an important area of research in various branches of Mathematics such as metric and topological spaces, theory of functions, approximation theory etc. Subsequently several authors have discussed various aspects of the theory and applications of fuzzy sets. The concept of fuzzyiness has...

The theory of fuzzy logic and the set has been successfully applied in various fields research social science, management mathematics. In this paper, we use concept Fuzzy real numbers to introduce study new double sequence spaces l∞ (M, λ, ρ), C F ρ) CoF defined by Orlicz function some their properties like linear space structure, completeness, solidness.

Random utility models have been widely used in many diverse fields. Considering utility as a random variable opened many new analytical doors to researchers in explaining behavioral phenomena. Introducing and incorporating the random error term into the utility function had several reasons, including accounting for unobserved variables. This paper incorporates fuzziness into random utility mode...

Since its introduction in the mid-sixties (Zadeh, L. A., (1965)), fuzzy set theory has gained recognition in a number of fields in the cases of uncertain, or qualitative or linguistically described system parameters or processes based on approximate reasoning, and has proven suitable and applicable with system describing rules of similar characteristics. It can be successfully applied with nume...

This paper presents a supervised training algorithm that implements fuzzy reasoning on a spiking neural network. Neuron selectivity is facilitated using receptive fields that enable individual neurons to be responsive to certain spike train frequencies and behave in a similar manner as fuzzy membership functions. The connectivity of the hidden and output layers in the fuzzy spiking neural netwo...

Well log data are routinely used for stratigraphic interpretation of the earth’s subsurface. This paper investigates using a co-evolutionary fuzzy system to generate a well log interpreter that can automatically process well log data and interpret reservoir permeability. The methodology consists of 3 steps: 1) transform well log data into fuzzy symbols which maintain the character of the origin...

Image segmentation plays an important role in image analysis. It is one of the first and most important tasks in image analysis and computer vision. This proposed system presents a variation of fuzzy cmeans algorithm that provides image clustering. Based on the Mercer kernel, the kernel fuzzy c-means clustering algorithm (KFCM) is derived from the fuzzy c-means clustering algorithm (FCM).The KF...

This work describes a novel fuzzy-sets-based method to solve a particular class of quadratic programming problems which have vagueness coefficients in the objective function. Quadratic programming problems are of utmost importance in an increasing variety of practical fields. In addition, as the ambiguity and vagueness are natural and ever-present in real-life situations requiring solutions, it...

The theory of fuzzy sets is used in various Mathematical fields. Zadeh [1] 1965 developed the concept of fuzzy sets which is the basis of fuzzy Mathematics. Since then various researchers worked on the development of fuzzy set theory. Atanassov [2,3,4,5,6,7] has given idea about intuitionistic fuzzy sets. Im and Lee [8] studied about the determinant of square intuitionistic fuzzy matrices (IFMs...

Fuzzy Logic has found popularity in the academic community and widespread use in the industry due to ever increasing complexities in systems, at the core of which lies vagueness, uncertainty and imprecision in information. The proposition of fuzzy set theory, specifically Fuzzy Inference Systems (FIS) led to an explosion of its application in diverse fields including manufacturing especially ma...