2020
DOI: 10.1155/2020/8384593
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LU Decomposition Scheme for Solving m-Polar Fuzzy System of Linear Equations

Abstract: This paper presents a new scheme for solving m-polar fuzzy system of linear equations (m-PFSLEs) by using LU decomposition method. We assume the coefficient matrix of the system is symmetric positive definite, and we discuss this point in detail with some numerical examples. Furthermore, we investigate the inconsistent m×nm-polar fuzzy matrix equation (m-PFME) and find the least square solution (LSS) of this system by using generalized inverse matrix theory. Moreover, we discuss the strong solution of m-polar … Show more

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Cited by 8 publications
(2 citation statements)
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References 38 publications
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“…We therefore look towards numerical iterative schemes which approximate the roots of fuzzy nonlinear equations. To approximate roots of fuzzy nonlinear equations, Abbsbandy and Asady [13] used Newton's method, Allahviranloo and Asari [14] used the Newton-Raphson method, Mosleh [15] used the Adomian decomposition method, and Ibrahim et al give the Levenberg-Marquest method (see also [16][17][18][19][20][21][22][23]). This research article is aimed at proposing efficient higher order iterative method as compared to well-known classical method, such as the Newton-Raphson method.…”
Section: F R ð þ = C: ð1þmentioning
confidence: 99%
“…We therefore look towards numerical iterative schemes which approximate the roots of fuzzy nonlinear equations. To approximate roots of fuzzy nonlinear equations, Abbsbandy and Asady [13] used Newton's method, Allahviranloo and Asari [14] used the Newton-Raphson method, Mosleh [15] used the Adomian decomposition method, and Ibrahim et al give the Levenberg-Marquest method (see also [16][17][18][19][20][21][22][23]). This research article is aimed at proposing efficient higher order iterative method as compared to well-known classical method, such as the Newton-Raphson method.…”
Section: F R ð þ = C: ð1þmentioning
confidence: 99%
“…erefore, in most of real world problems, the parameters involved in the system or variables of the nonlinear equations are presented by a fuzzy number. e concepts of fuzzy numbers and arithmetic operation with fuzzy numbers were first introduced and investigated in [1][2][3][4][5][6][7][8][9][10]. Hence, it is necessary to approximate the root of fuzzy nonlinear equation:…”
Section: Introductionmentioning
confidence: 99%