2009
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SOLUTION OF FUZZY DIFFERENTIAL EQUATIONS UNDER GENERALIZED DIFFERENTIABILITY BY ADOMIAN DECOMPOSITION METHOD
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2
Adomian decomposition method has been applied to solve many functional equations so far. In this article, we have used this method to solve the fuzzy differential equation under generalized differentiability. We interpret a fuzzy differential equation by using the strongly generalized differentiability. Also one concrete application for ordinary fuzzy differential equation with fuzzy input data are given.
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57
75


T.
Allahviranloo
Department of Mathematics, Science and Research Branch, Islamic Azad
University,Tehran, 14778, Iran
Department of Mathematics, Science and Research
Iran


L.
Jamshidi
Department of Mathematics, Science and Research Branch, Islamic Azad
University,Tehran, 14778, Iran
Department of Mathematics, Science and Research
Iran
Adomian decomposition method
GENERALIZATIONS OF THE DIFFERENTIABILITY OF FUZZY DIFFERENTIAL EQUATIONS
DESIGNING AN OPTIMIZATION MODEL FOR PREVENTING THE WASTE TIME IN THE ACTIVITY CYCLE OF AN ORGANIZATION
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2
This article proposes an optimization model for preventing the waste of time in the educational and research activities' cycle of an organization such as a university. For this purpose and in order to increase efficiency and prevent the waste of time; the graph theory models have been used. The educational and research activities diagrams of a supposed university is drawn by the use of graphs theory model, and then these graphs are analyzed, then in order to design a model, the units, activities and the time of doing each activity are symbolized, and the collected data are presented in the form of matrix. In this article two procedures are suggested for optimization; using subgraphs for every activity cycle in order to shorten the activity cycles and minimizing the time of doing each work. The algorithm of time minimizing is based on recognizing and determining the edges with the most weight as the maximum time. Also the influential factors on the waste of time in activity cycle are recognized and then replaced or omitted.
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76
89


M.
Taleghani
Department of post – graduate Islamic Azad university, Rasht, Iran
Department of post – graduate Islamic
Iran
taleghani@iaurasht.ac.ir


Y.
Modabbernia
Department of post – graduate Islamic Azad university, Rasht, Iran
Department of post – graduate Islamic
Iran
Graph Theory
SUBGRAPH
optimization
ACTIVITY CYCLE
UNIT
WORK
WORKING TIME
THE USE OF SEMI INHERITED LU FACTORIZATION OF MATRICES IN INTERPOLATION OF DATA
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2
The polynomial interpolation in one dimensional space R is an important method to approximate the functions. The Lagrange and Newton methods are two well known types of interpolations. In this work, we describe the semi inherited interpolation for approximating the values of a function. In this case, the interpolation matrix has the semi inherited LU factorization.
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90
106


MOHAMMAD ALI
FARIBORZI ARAGHI
Department of mathematics, Islamic Azad University,Central Tehran Branch,
Tehran, Iran
Department of mathematics, Islamic Azad University
Iran
mafa_i@yahoo.com


Amir
Fallahzadeh
Department of mathematics, Islamic Azad University,Central Tehran Branch,
Tehran, Iran
Department of mathematics, Islamic Azad University
Iran
SEMI INHERITED LU FACTORIZATION
INTERPOLATION MATRIX
SEMI INHERITED INTERPOLATION