in this paper we have generalized the concepts of ,q-fuzzy ideals, ,q-fuzzy quasi-ideals and,q-fuzzy bi-ideals by introducing the concepts of   k ,q -fuzzy ideals,   k ,q -fuzzy quasiideals and   k ,q -fuzzy bi-ideals in ternary semigroups and several related properties are investigated. different characterizations of regular and weakly regular ternary semigroups b...

Fuzzy control and modeling use only a small portion of the fuzzy mathematics that is available; this portion is also mathematically quite simple and conceptually easy to understand. In this chapter, we introduce some essential concepts, terminology, notations, and arithmetic of fuzzy sets and fuzzy logic. We include only a minimum though adequate amount of fuzzy mathematics necessary for unders...

Load sensor is developed using fuzzy logic as well as neuro-fuzzy method. It is two inputs and one output sensor. Both fuzzy logic and neuro-fuzzy algorithms are simulated using MATLAB fuzzy logic toolbox. This paper outlines the basic difference between the results of fuzzy logic and neuro-fuzzy algorithms and provides the better algorithm for load sensor. Index Terms —fuzzy logic, load sensor...

A geometrical approach to validation of fuzzy temporal relations between fuzzy time primitives, based on the possibility and necessity measures are proposed. Fuzzy temporal relations between fuzzy time points and fuzzy time point and fuzzy time interval are considered. The same approach can be used for evaluation of relation between two fuzzy intervals. An example of validation of temporal rela...

Both Takagi–Sugeno (TS) and Mamdani fuzzy systems are known to be universal approximators. In this paper, we investigate whether one type of the fuzzy approximators is more economical than the other type. The TS fuzzy systems in this study are the typical two-input single-output TS fuzzy systems: they employ trapezoidal or triangular input fuzzy sets, arbitrary fuzzy rules with linear rule cons...

in applications there occur different forms of uncertainty. the twomost important types are randomness (stochastic variability) and imprecision(fuzziness). in modelling, the dominating concept to describe uncertainty isusing stochastic models which are based on probability. however, fuzzinessis not stochastic in nature and therefore it is not considered in probabilisticmodels.since many years t...

After introducing and developing fuzzy set theory, a lot of studies have been done to combine statistical methods and fuzzy set theory. This works, called fuzzy statistics, have been developed in some branches. In this article we review essential works on fuzzy estimation, fuzzy hypotheses testing, fuzzy regression, fuzzy Bayesian statistics, and some relevant fields. Zusammenfassung: Nach Entw...

We inquire further into the properties on fuzzy closed ideals. We give a characterization of a fuzzy closed ideal using its level set, and establish some conditions for a fuzzy set to be a fuzzy closed ideal. We describe the fuzzy closed ideal generated by a fuzzy set, and give a characterization of a finite-valued fuzzy closed ideal. Using a t-norm T , we introduce the notion of (imaginable) T...

In this paper we establish equivalence between a theory of fuzzy functional dependences and a fragment of fuzzy logic. We give a way to interpret fuzzy functional dependences as formulas in fuzzy logic. This goal is realized in a few steps. Truth assignment of attributes is defined in terms of closeness between two tuples in a fuzzy relation. A corresponding fuzzy formula is associated to a fuz...