In this paper, the method of least squares is applied to the fuzzy inference rules. We begin studying the conditions in which from a fuzzy set we can build another through the method of least squares. Then we apply this technique in order to evaluate the conclusions of the generalized modus ponens. We present different theorems and examples that demonstrate the fundamental advantages of the method studied.
In this paper we study the effect of Atanassov's operator on the properties of properties reflexive, symmetric, antisymmetric, perfect antisymmetric and transitive intuitionistic fuzzy relations. We finish the paper analysing the partial enclosure of the intuitionistic fuzzy relations and its effect on the conservation of the transitive property through Atanassov's operator.
This paper introduces the concept of intuitionistic fuzzy relation. We also study the choice of t-norms and t-conorms which must be done in order that the composition of intuitionistic fuzzy relations fulfils the largest number of properties. On the other hand, we also analyse the intuitionistic fuzzy relations in a set and their properties. Besides, we also study the properties of the intuitionistic fuzzy relations in a set and the properties of the composition with different t-norms and t-conorms....
Firstly we present a geometric interpretation of interval-valued fuzzy sets. Secondly, we apply the method of least squares to the fuzzy inference rules when working with these sets. We begin approximating the lower and upper extremes of the membership intervals to axb type functions by means of the method of least squares. Then we analyze a technique for evaluating the conclusion of the generalized modus ponens and we verify the fulfillment of Fukami and alumni axioms [9].
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