نتایج جستجو برای: fuzzy difference equations

تعداد نتایج: 729155  

2011
Juan Carlos Díaz Jesús Medina

Fuzzy relation equations are used to investigate theoretical and applicational aspects of fuzzy set theory, e.g., approximate reasoning, time series forecast, decision making and fuzzy control, etc.. This paper relates these equations to a particular kind of concept lattices.

2007
Giovanni Vincenti Goran Trajkovski

Fuzzy mediation is an innovative approach to the creation of a framework geared towards supervised and collaborative learning in systems with two controllers, one being an expert controller and the second being a novice one. The nature of fuzzy sets allows for the comparison of inputs to reach a consensus on the overall difference between the controls. In previous works we have highlighted the ...

Journal: :CoRR 2011
Stefano Panzieri Gabriele Oliva Roberto Setola

In this paper the Distributed Consensus and Synchronization problems with fuzzy-valued initial conditions are introduced, in order to obtain a shared estimation of the state of a system based on partial and distributed observations, in the case where such a state is affected by ambiguity and/or vagueness. The Discrete-Time Fuzzy Systems (DFS) are introduced as an extension of scalar fuzzy diffe...

2016
Ch. Vasavi G. Suresh Kumar M.S.N. Murty

Using the concept of Hukuhara difference, in this paper we introduce a class of new derivatives called Hukuhara delta derivative and a class of new integrals called Hukuhara delta integral for fuzzy setvalued functions on time scales. Moreover, some corresponding properties of Hukuhara delta derivative and Hukuhara delta integral are discussed. Furthermore, sufficient conditions are established...

Journal: :CoRR 2009
Nizami Gasilov Sahin Emrah Amrahov Afet Golayoglu Fatullayev

In this paper, systems of linear differential equations with crisp real coefficients and with initial condition described by a vector of fuzzy numbers are studied. A new method based on geometric representations of linear transformations is proposed to find a solution. The most important difference between this method and methods offered in other papers is that the solution is considered to be ...

2006
Martin Štěpnička Lenka Nosková

Inference mechanisms and interpretations of fuzzy rule bases are studied together from the point of view of systems of fuzzy relation equations. A proper use of an inference mechanism connected to a fuzzy relation interpreting a fuzzy rule base is certified by keeping the fundamental interpolation condition. The paper aims at new solutions of systems of fuzzy relation equations which are motiva...

2016
A. Ramli R. R. Ahmad U. K. S. Din A. R. Salleh

In this paper a third-order composite Runge Kutta method is applied for solving fuzzy differential equations based on generalized Hukuhara differentiability. This study intends to explore the explicit methods which can be improved and modified to solve fuzzy differential equations. Some definitions and theorem are reviewed as a basis in solving fuzzy differential equations. Some numerical examp...

2003
Siegfried Gottwald

For theoretical fuzzy control it is a well known strategy to transform a system of control rules into a system of relation equations. Because these systems of relation equations are not always solvable, solvability criteria and approximate solutions have been discussed. We reconsider some of the results in this field and extend them using more recent results on t-norm based fuzzy logics and on ...

2007
Martin Stepnicka Bernard De Baets Lenka Nosková

Systems which use a fuzzy rule base and an inference mechanisms are quite frequently used in many applications. Fuzzy rules and inference mechanisms can be described by a system of fuzzy relation equations. A solution to a given system of fuzzy relation equations can serve us a proper model of fuzzy rules (fuzzy model for short). But only two particular solutions, let us call them disjunctive a...

Journal: :IEEE Trans. Fuzzy Systems 2002
Phil Diamond

Formulations of fuzzy integral equations in terms of the Aumann integral do not reflect the behavior of corresponding crisp models. Consequently, they are ill-adapted to describe physical phenomena, even when vagueness and uncertainty are present. A similar situation for fuzzy ODEs has been obviated by interpretation in terms of families of differential inclusions. The paper extends this formal...

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