Fuzzy operators are an essential tool in many fields and the operation of composition is often needed. In general, composition is not a commutative operation. However, it is very useful to have operators for which the order of composition does not affect the result. In this paper, we analyze when permutability appears. That is, when the order of application of the operators does not change the ...

In this work, we introduce the concept of fuzzy parameterized intervalvalued fuzzy soft set theory (fpivfss) and study their operations. We then define fpivfss-aggregation operator to form fpivfss-decision making method that allows constructing more efficient decision processes. Finally, some numerical examples are employed to substantiate the conceptual arguments.

This paper is based on the development of fuzzy Logic based edge detection techniques in digital images. The proposed technique used Sobel operator, Zernike moment operator, and Fuzzy inference system in combination for edge detection purpose. Edge is a boundary between two homogeneous regions. Edge detection refers to the process of identifying and locating sharp discontinuities in an image. I...

The growth in amount of data available today has encouraged the development of effective data analysis methods to support human decision-making. Neuro-fuzzy computation is a soft computing hybridisation combining the learning capabilities of the neural networks with the linguistic representation of data provided by the fuzzy models. In this paper, a framework to build temporally local neuro-fuz...

This paper presents a survey on methods for solving fuzzy linear programs. First LP models with soft constraints are discussed. Then LP problems in which coefficients of constraints and/or of the objective function may be fuzzy are outlined. Pivotal questions are the interpretation of the inequality relation in fuzzy constraints and the meaning of fuzzy objectives. In addition to the commonly a...

We study interior operators and interior structures in a fuzzy setting. We investigate systems of “almost open” fuzzy sets and the relationships to fuzzy interior operators and fuzzy interior systems.

Soft set theory [1] was firstly introduced byMolodtsov in 1999 as a general mathematical tool for dealing with uncertain, fuzzy, not clearly defined objects. He has shown several applications of this theory in solvingmany practical problems in economics, engineering, social science, medical science, and so forth, in [1]. In the recent years, papers about soft sets theory and their applications ...

Recently, a precise and stable machine learning algorithm, i.e. eigenvalue classification method (EigenClass), has been developed by using the concept of generalised eigenvalues in contrast to common approaches, such as k-nearest neighbours, support vector machines, decision trees. In this paper, we offer new algorithm called fuzzy parameterized soft aggregation classifier (FPFS-AC) combine mod...

Ronald R. Yager Machine Intelligence Institute, Iona College New Rochelle, NY 10801 [email protected] (212)249-2047 ABSTRACT Fuzzy sets and other methods have been used to model a softening of constraints in CP problems. Here we suggest an approach to the softening of the CP problem at the meta level, the process used to aggregate the satisfactions to the individual constraints. We suggest the us...