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Articles 1 - 27 of 27
Full-Text Articles in Physical Sciences and Mathematics
A Numerical Approach On Hiemenz Ow Problem Using Radial Basis Functions, Saeid Abbasbandy, K. Parand, S. Kazem, A. R. Sanaei Kia
A Numerical Approach On Hiemenz Ow Problem Using Radial Basis Functions, Saeid Abbasbandy, K. Parand, S. Kazem, A. R. Sanaei Kia
Saeid Abbasbandy
In this paper, we propose radial basis functions (RBF) to solve the two dimensional flow of fluid near a stagnation point named Hiemenz flow. The Navier-Stokes equations governing the flow can be reduced to an ordinary diferential equation of third order using similarity transformation. Because of its wide applications the ow near a stagnation point has attracted many investigations during the past several decades. We satisfy boundary conditions such as infinity condition, by using Gaussian radial basis function through the both diferential and integral operations. By choosing center points of RBF with shift on one point in uniform grid, we …
Interpolation Of Fuzzy Data By Using Quadratic Piecewise Polynomial Induced Form E(3) Cubic Splines, H. Behforooz, R. Ezzati, Saeid Abbasbandy
Interpolation Of Fuzzy Data By Using Quadratic Piecewise Polynomial Induced Form E(3) Cubic Splines, H. Behforooz, R. Ezzati, Saeid Abbasbandy
Saeid Abbasbandy
In this paper, we will consider the interpolation of fuzzy data by using the fuzzy-valued piecewise quartic polynomials Qy0,y1,..., yn (x) induced from E(3) cubic spline functions.
Effective Calculation Of Multiple Solutions Of Mixed Convection In A Porous Medium, Saeid Abbasbandy, E. Shivanian
Effective Calculation Of Multiple Solutions Of Mixed Convection In A Porous Medium, Saeid Abbasbandy, E. Shivanian
Saeid Abbasbandy
This paper considers an important model of boundary value problem with a condition at infinity namely combined free and forced convection over a plane of arbitrary shape embedded in a fluid-saturated porous medium; this model admits dual solutions, and uses a technique, which is to some extent modification of homotopy analysis method (HAM), in order to obtain dual solutions analytically with high accuracy.
An Improvement In Centroid Point Method For Ranking Of Fuzzy Numbers, Saeid Abbasbandy, T. Hajjari
An Improvement In Centroid Point Method For Ranking Of Fuzzy Numbers, Saeid Abbasbandy, T. Hajjari
Saeid Abbasbandy
In many applications, ranking of fuzzy numbers is an important component of the decision process. Many authors have investigated the use of fuzzy sets in ranking alternatives and they have studied different methods of raking fuzzy sets. Particularly, the ranking of fuzzy numbers. In a paper by Cheng [A new approach for ranking fuzzy numbers by distance method, Fuzzy Sets and Systems 95 (1998) 307-317], a centroid-based distance method was suggested for ranking fuzzy numbers, both normal and non-normal. The method utilizes the Euclidean distances from the origin to the centroid point of each fuzzy numbers to compare and rank …
Solution Of Fully Fuzzy Linear Systems By St Method, M. Mosleh, M. Otadi, Saeid Abbasbandy
Solution Of Fully Fuzzy Linear Systems By St Method, M. Mosleh, M. Otadi, Saeid Abbasbandy
Saeid Abbasbandy
In this paper, we investigate the existence of a positive solution of fully fuzzy linear equation systems where fuzzy coefficient matrix is a positive matrix. This paper mainly discusses a new decomposition of a nonsingular fuzzy matrix, a symmetric matrix times to a triangular (ST) decomposition. By this decomposition, every nonsingular fuzzy matrix can be represented as a product of a fuzzy symmetric matrix S and a fuzzy triangular matrix T.
A Method For Solving Fully Fuzzy Linear System, M. Mosleh, Saeid Abbasbandy, M. Otadi
A Method For Solving Fully Fuzzy Linear System, M. Mosleh, Saeid Abbasbandy, M. Otadi
Saeid Abbasbandy
In this paper, a numerical method for finding minimal solution of a m*n fully fuzzy linear system of the form Ax=b based on pseudo inverse calculation, is given when the central matrix of coeficients is row full rank or column full rank, and where A is a non-negative fuzzy m*n matrix, the unknown vector x is a vector consisting of n non-negative fuzzy numbers and the constant b is a vector consisting of m non-negative fuzzy numbers.
Solving Fuzzy Linear System By Fuzzy Neural Network And Applications In Economics, M. Otadi, M. Mosleh, Saeid Abbasbandy
Solving Fuzzy Linear System By Fuzzy Neural Network And Applications In Economics, M. Otadi, M. Mosleh, Saeid Abbasbandy
Saeid Abbasbandy
In this paper, a novel hybrid method based on fuzzy neu- ral network for estimate fuzzy coefficients (parameters) of fuzzy linear supply and demand function, is presented. Here a neural network is considered as a part of a large field called neural computing or soft computing. Moreover, in order to find the approximate parameters, a simple algorithm from the cost function of the fuzzy neural network is proposed.
Solving Fuzzy Differential Inclusions Using The Lu-Representation Of Fuzzy Numbers, Saeid Abbasbandy, A. Panahi, H. Rouhparvar
Solving Fuzzy Differential Inclusions Using The Lu-Representation Of Fuzzy Numbers, Saeid Abbasbandy, A. Panahi, H. Rouhparvar
Saeid Abbasbandy
In this paper, the solution of fuzzy differential inclusions with lower-upper representation is established.
Canonical Representation For Approximating Solution Of Fuzzy Polynomial Equations, M. Salehnegad, Saeid Abbasbandy, M. Mosleh, M. Otadi
Canonical Representation For Approximating Solution Of Fuzzy Polynomial Equations, M. Salehnegad, Saeid Abbasbandy, M. Mosleh, M. Otadi
Saeid Abbasbandy
No abstract provided.
Numerical Solution Of Fuzzy Differential Inclusion By Euler Method, E. Babolian, Saeid Abbasbandy, M. Alavi
Numerical Solution Of Fuzzy Differential Inclusion By Euler Method, E. Babolian, Saeid Abbasbandy, M. Alavi
Saeid Abbasbandy
In this paper we introduce Euler method for solving one dimensional fuzzy differential inclusions. Fuzzy reachable set can be approximated by Euler method with complete analysis.
Fixed Point Method For Solving Fuzzy Nonlinear Equations, Saeid Abbasbandy, Ahmad Jafarian
Fixed Point Method For Solving Fuzzy Nonlinear Equations, Saeid Abbasbandy, Ahmad Jafarian
Saeid Abbasbandy
In this paper, we propose the numerical soluiton for a fuzzy nonlinear equation by fixed point method.
Newton's Method For Solving A System Of Dual Fuzzy Nonlinear Equations, Saeid Abbasbandy
Newton's Method For Solving A System Of Dual Fuzzy Nonlinear Equations, Saeid Abbasbandy
Saeid Abbasbandy
In this paper, we propose a numerical solution for a system of dual fuzzy nonlinear equations by Newton’s method. The fuzzy quantities are presented in parametric form. Some numerical illustrations are given to show the efficiency of algorithm.
Approximation Of Fuzzy Functions By Distance Method, S. Abbasbandy, M. Amirfakhrian
Approximation Of Fuzzy Functions By Distance Method, S. Abbasbandy, M. Amirfakhrian
Saeid Abbasbandy
Approximation of functions in a given space is an old problem in applied mathematics. In this paper the problem is considered for fuzzy data and fuzzy functions using the defuzzification function introduced by Fortemps and Roubens. We introduce a fuzzy polynomial approximation as D-approximation of a fuzzy function on a discrete set of points and we present a method to compute it.
Ranking Of Fuzzy Numbers By Min Distance, S. Abbasbandy, M. Otadi, M. Mosleh
Ranking Of Fuzzy Numbers By Min Distance, S. Abbasbandy, M. Otadi, M. Mosleh
Saeid Abbasbandy
Several different strategies have been proposed for ranking of fuzzy numbers. These include methods based on the coefficient of variation (CV index), distance between fuzzy sets, centroid point and original point, and weighted mean value. Each of these techniques has been shown to produce non-intuitive results in certain cases. In this paper we propose a ranking method for fuzzy numbers by min distance. The method for ranking fuzzy numbers suggested in this paper is based on comparison of distance from fuzzy numbers to fuzzy minimum where fuzzy minimum is a reference set and this method able to overcome the shortcomings …
Crisp Solution Of A General Fuzzy Linear System, S. Abbasbandy, R. Ezzati
Crisp Solution Of A General Fuzzy Linear System, S. Abbasbandy, R. Ezzati
Saeid Abbasbandy
In this paper a method for solving a general fuzzy linear system with crisp solution is considered. We consider the method in special case when the elements of the coefficient matrix and the right hand side are trapezoidal fuzzy numbers. The method in detail is discussed and followed by theorem and illustrated by solving some examples.
A Posteriori Estimate For Tikhonov Regularization Parameter, S. Abbasbandy
A Posteriori Estimate For Tikhonov Regularization Parameter, S. Abbasbandy
Saeid Abbasbandy
This paper deals the numerical solution of integral equations of the first kind with using regularization method. There are many stopping rules based on discrepancy principle or discussed in [3]. Here a new stopping rule is described which uses SVD (Singular Value Decomposition) and condition number of matrices. Finally, we give a number of numerical examples showing that the method works well in practice.
A Method For Solving Fuzzy Linear Systems, S. Abbasbandy, M. Alavi
A Method For Solving Fuzzy Linear Systems, S. Abbasbandy, M. Alavi
Saeid Abbasbandy
In this paper we present a method for solving fuzzy linear systems by two crisp linear systems. Also necessary and sufficient conditions for existence of solution are given. Some numerical examples illustrate the efficiency of the method.
A New Method For Solving Symmetric Fuzzy Linear Systems, S. Abbasbandy, M. Alavi
A New Method For Solving Symmetric Fuzzy Linear Systems, S. Abbasbandy, M. Alavi
Saeid Abbasbandy
In this paper we represent a new method for solving a symmetric fuzzy linear system by two crisp linear systems. Also necessary and sufficient conditions for the solution existence are given.
A New Method For Ranking Of Fuzzy Numbers Through Using Distance Method, S. Abbasbandy, C. Lucas, B. Asady
A New Method For Ranking Of Fuzzy Numbers Through Using Distance Method, S. Abbasbandy, C. Lucas, B. Asady
Saeid Abbasbandy
In this paper, by using a new approach on distance between two fuzzy numbers, we construct a new ranking system for fuzzy number which is very realistic and also matching our intuition as the crisp ranking system on R.
Fuzzy Interpolation, S. Abbasbandy
Fuzzy Interpolation, S. Abbasbandy
Saeid Abbasbandy
In this paper, we will consider the interpolation of fuzzy data by a continuous fuzzy-valued function. We will use Lagrange polynomials, natural splines and complete splines.
Numerical Solution Of Fuzzy Differential Equation By Runge-Kutta Method, S. Abbasbandy, T. Allah Viranloo
Numerical Solution Of Fuzzy Differential Equation By Runge-Kutta Method, S. Abbasbandy, T. Allah Viranloo
Saeid Abbasbandy
In this paper numerical algorithms for solving 'fuzzy ordinary differential equations' are considered. A scheme based on the 4th Runge-Kutta method in detail is discussed and this is followed by a complete error analysis. The algorithm is illustrated by solving some linear and nonlinear fuzzy Cauchy problems.
Numerical Solution Of Fuzzy Differential Equation By Runge-Kutta Method Of Order 2, S. Abbasbandy, T. Allah Viranloo
Numerical Solution Of Fuzzy Differential Equation By Runge-Kutta Method Of Order 2, S. Abbasbandy, T. Allah Viranloo
Saeid Abbasbandy
In this paper numerical algorithms for solving 'fuzzy ordinary differential equations' are considered. A scheme on the 2nd Rung-Kutta method in detail is discussed and this is followed by a complete error analysis. The algorithm is illustrated by solving some linear and nonlinear fuzzy Cauchy problems.
An Augmented Galerkin Method For Singular Integral Equations With Hilbert Kernel, S. Abbasbandy, E. Babolian
An Augmented Galerkin Method For Singular Integral Equations With Hilbert Kernel, S. Abbasbandy, E. Babolian
Saeid Abbasbandy
In recent papers, Delves [2] and others [1], [3] described a Chebyshev series method for the numerical solution of integral equations with non-singular kernels or some particular singular kernels, for example Green's function kernel, logarithmic and Cauchy kernels and so on. In this paper we describe a Fourier series expansion method for a class of singular integral equations with Hilbert kernel and constant coefficients. We give a number of numerical examples showing that Galerkin method works well in practice.
Orthogonalization Process Or Finding A Basic Feasible Solution (Bfs), G.R. Jahanshahloo, S. Abbasbandy
Orthogonalization Process Or Finding A Basic Feasible Solution (Bfs), G.R. Jahanshahloo, S. Abbasbandy
Saeid Abbasbandy
For finding an optimal solution in L.P., combination of orthogonality and simplex method is used. It seems that the number of iteration is reduced with respect to new algorithm in [1].
An Augmented Galerkin Algorithms For First Kind Integral Equations Of Hammerstein Type, S. Abbasbandy, E. Babolian
An Augmented Galerkin Algorithms For First Kind Integral Equations Of Hammerstein Type, S. Abbasbandy, E. Babolian
Saeid Abbasbandy
Recent papers, [1],[2] & [3], describe some algorithms for linear first kind integral equations. These algorithms are based on augmented Galerkin method and Cross-validation scheme [5]. The results show that, these algorithms work well for linear equations. In this paper we apply algorithms of [1] & [2] on non-linear first kind integral equations of Hammerstein type with bounded solution. In order to obtain a posteriori error estimate, we apply fifteen-point Gauss-Kronrod quadrature rule [4]. Finally, we give a number of numerical examples showing that the algorithms work well in practice.
Automatic Augmented Galerkin Algorithms For Linear First Kind Integral Equations: Non-Singular And Weak Singular Kernels, S. Abbasbandy, E. Babolian
Automatic Augmented Galerkin Algorithms For Linear First Kind Integral Equations: Non-Singular And Weak Singular Kernels, S. Abbasbandy, E. Babolian
Saeid Abbasbandy
In this paper we describe some iterative algorithms for computing these paramteres for non-singular and weak-singular first kind integral equations. We give also error estimates which are easily computed. Finally, we give a number of numerical examples showing that these algorithms work well in practice and netter than methods presented in [2],[3] and [8].
Combination Of Orthogonality And Simplex Method For Solving Linear Programming, G.R. Jahanshahloo, S. Abbasbandy
Combination Of Orthogonality And Simplex Method For Solving Linear Programming, G.R. Jahanshahloo, S. Abbasbandy
Saeid Abbasbandy
For obtaining an optimal solution in L.P. combination of orthogonality and simplex method is used. It seems that the number of iteration is reduced.