Max-Min averaging operator: fuzzy inequality systems and resolution
Authors
Abstract:
Minimum and maximum operators are two well-known t-norm and s-norm used frequently in fuzzy systems. In this paper, two different types of fuzzy inequalities are simultaneously studied where the convex combination of minimum and maximum operators is applied as the fuzzy relational composition. Some basic properties and theoretical aspects of the problem are derived and four necessary and sufficient conditions are presented. Moreover, an algorithm is proposed to solve the problem and an example is described to illustrate the algorithm.
similar resources
Adaptive resolution min-max classifiers
A high automation degree is one of the most important features of data driven modeling tools and it should be taken into consideration in classification systems design. In this regard, constructive training algorithms are essential to improve the automation degree of a modeling system. Among neuro-fuzzy classifiers, Simpson's (1992) min-max networks have the advantage of being trained in a cons...
full textRESOLUTION OF NONLINEAR OPTIMIZATION PROBLEMS SUBJECT TO BIPOLAR MAX-MIN FUZZY RELATION EQUATION CONSTRAINTS USING GENETIC ALGORITHM
This paper studies the nonlinear optimization problems subject to bipolar max-min fuzzy relation equation constraints. The feasible solution set of the problems is non-convex, in a general case. Therefore, conventional nonlinear optimization methods cannot be ideal for resolution of such problems. Hence, a Genetic Algorithm (GA) is proposed to find their optimal solution. This algorithm uses th...
full textInseparability of Min-max Systems
Min-max systems, or min-max-plus systems are algebraic models of Discrete Event Dynamic Systems. They are non-linear extension of the well known linear max-plus system models. In this paper, we survey our recent research results related to the structural property ”inseparability” of min-max systems proposed in [24]. It turns out inseparability has very interesting relationship to many aspects o...
full textVariable operator technique and the min-max theorem
Abstract. We investigate a variation method where the trial function is generated from the application of a variable operator on a reference function. Two conditions are identified, one for obtaining a maximum and another for a minimum. Although the conditions are easy to understand, the overall formulation is somewhat unusual as each condition gives rise to a two-step variation process. As an ...
full textMax-min Intuitionistic Fuzzy Matrix of an Intuitionistic Fuzzy Graph
In this paper we introduce the Max-Min intuitionistic fuzzy matrix M (G) of an intuitionistic fuzzy graph. And the extreme energy of M (G) is defined. And also we give the explicit expression for the coefficients of the characteristic polynomial of M (G) . These concepts are illustrated with real time example. AMS Subject Classification: 03E72, 05C50
full textOn fuzzy-rough attribute selection: Criteria of Max-Dependency, Max-Relevance, Min-Redundancy, and Max-Significance
Attribute selection is one of the important problems encountered in pattern recognition, machine learning, data mining, and bioinformatics. It refers to the problem of selecting those input attributes or features that are most effective to predict the sample categories. In this regard, rough set theory has been shown to be successful for selecting relevant and nonredundant attributes from a giv...
full textMy Resources
Journal title
volume 51 issue 1
pages 55- 70
publication date 2019-06-01
By following a journal you will be notified via email when a new issue of this journal is published.
Hosted on Doprax cloud platform doprax.com
copyright © 2015-2023