In this paper, first, we propose Kaucher arithmetic for INTERVAL number and then solve the system A2n×nXn×1=b2n×1 where aij= [ai,j,`ai,j] and xj= [xj,`xj] and bi= [bi,`bi] based on Kaucher arithmetic such that ai,j .`ai,j ³ 0. Then, we extend this method by use of a- level set for fully fuzzy system of A~2n×nX~n×1= b~2n×1.

In this paper we find solution of LINEAR INTERVAL EQUATION in dual form based on the generalized procedure of INTERVAL extension which is called INTERVAL extended zero method.Moreover, proposed method has significant advantage, is that it substantially decreases the excess width effect.

In this paper, we intend to solve special kind of ordinary differential EQUATIONs which is called Heun EQUATIONs, by converting to a corresponding stochastic differential EQUATION (S.D.E.). So, we construct a stochastic LINEAR EQUATION system from this EQUATION which its solution is based on computing fundamental matrix of this system and then, this S.D.E. is solved by numerically methods. Moreover, its asymptotic stability and statistical concepts like expectation and variance of solutions are discussed. Finally, the attained solutions of these S.D.E.s compared with exact solution of corresponding differential EQUATIONs.

In most of real world problems data su er from inaccuracy, thus considering an INTERVAL for data perturbation seems to be a good idea. There exist many papers in literature about INTERVAL LINEAR programming problems (ILP) dealing with non negative variables. Here the general form of an ILP is considered where all the parameters and variables are considered to be INTERVALs. Moreover, in this study more general conditions for variables are considered, variables which are unrestricted in sign. Although this is the case in most of the real world problems, due to high complexity it has not been dealt with in literature yet. In this paper a new method is presented in order to obtain fully INTERVAL LINEAR programming problems (F ILPP ) using a nonLINEAR programming problem (NLP). Furthermore, in order to demonstrate how the proposed method works two numerical examples are illustrated.

In this paper, the fuzzy matrix EQUATION AeX B = e C in which A; B are n × n crisp matrices respectively and e C is an n×n arbitrary LR fuzzy numbers matrix, is investigated. A new numerical procedure for calculating the fuzzy solution is designed and a suffcient condition for the existence of strong fuzzy solution is derived. Some examples are given to illustrate the proposed method.