Gupta and Ray (Fuzzy Sets and Systems 54 (1993) 191) introduced the notion of fuzzy projective planes. We show that an old theorem of Dembowski classi$es all $nite fuzzy projective planes, that the examples in Gupta and Ray (Fuzzy Sets and Systems 54 (1993) 191) arise from ordinary projective planes and have much easier descriptions that can easily be generalized, and that there exist fuzzy pro...

Fuzzy systems of linear equations play a vital role in various applications of engineering, science and finance problems. This paper proposes a new method for solving Fully Fuzzy System of Linear Equations (FFSLE) using the linear programming problem approach. There is no restriction on the elements of coefficient matrix. The proposed method is able to solve the system, when the elements of the...

Optimization is a procedure of finding and comparing feasible solutions until no better solution can be found. It can be divided into several fields, one of which is the Convex Optimization. It is characterized by a convex objective function and convex constraint functions over a convex set which is the set of the decision variables. This can be viewed, on the one hand, as a particular case of ...

This paper investigates the numerical solution of imprecisely defined fractional order dynamic system, subjected to an unit impulse load. A mechanical spring mass system having fractional damping of order 1/2 with fuzzy initial condition is taken into consideration. Fuzziness appearing in the initial conditions is modelled through different types of convex normalised fuzzy sets viz. triangular,...

This paper deals with boolean linear programming problems involving coefficients in the objective function as fuzzy numbers. In the study of these problems different approaches can be proposed to use ranking fuzzy numbers methods and fuzzy preference relations obtaining auxiliary classical boolean programming problems, and to use the representation theorem obtaining a convex set with extreme po...

‎let $x$ be a real normed  space, then  $c(subseteq x)$  is  functionally  convex  (briefly, $f$-convex), if  $t(c)subseteq bbb r $ is  convex for all bounded linear transformations $tin b(x,r)$; and $k(subseteq x)$  is  functionally   closed (briefly, $f$-closed), if  $t(k)subseteq bbb r $ is  closed  for all bounded linear transformations $tin b(x,r)$. we improve the    krein-milman theorem  ...

In this paper we address the issue of providing a geometrical characterization for the decision problem of asking whether a partial assignment β : fi 7→ αi mapping fuzzy events fi into real numbers αi (i = 1, . . . , n) extends to a generalized belief function on fuzzy sets, according to a suitable definition. We will characterize this problem in a way that allows to treat it as the membership ...

Powerset structures of extensional fuzzy sets in sets with similarity relations are investigated. It is proved that extensional fuzzy sets have powerset structures which are powerset theories in the category of sets with similarity relations, and some of these powerset theories are defined also by algebraic theories (monads). Between Zadeh's fuzzy powerset theory and the classical powerset theo...