Numerous authors have proposed dierent approaches to nd the solution
of fuzzy nonlinear systems with fuzzy coecients involving fuzzy variables.
Nevertheless, the famous iterative method is Newton's approach. It is im-
portant to mention that, [14] presented a Newton's method for solving fuzzy
nonlinear equations, which was extended to solve dual fuzzy nonlinear systems
by [10]. In the work of [6] the numerical solution of fuzzy nonlinear systems via
steepest descent scheme has been presented. Via midpoint approach on New-
ton's method, [16] proposed an iterative method for solving fuzzy nonlinear
systems. Dierent approaches for solving fuzzy nonlinear systems have also
been given by many researchers, such as [1], [7] etc. All the existing methods
are based on Newtonian approach. It is remarkable to point out that, the
major weakness of Newton's method arise from the non- singularity of the Ja-
cobian matrix in the neighborhood of the solution for successful quadratic rate
of convergence [2] . Violating this condition, i.e. the Jacobian to be singular
the convergence is too slow and may even be lost. Based on this fact, Newton's-
type method that required Jacobian computation may not be suitable always
for solving singular fuzzy nonlinear equations. This is what motivates us to
suggest a new approach for solving singular fuzzy nonlinear equations. The
anticipation has been to bypass the point at which the Jacobian is singular.
The method proposed in this work is computationally cheaper than Classical
Newton's method. This paper has been arranged as follows; we present brief
overview and some basic denitions of the fuzzy nonlinear equations in section
2, description of Newton's method is given in section 3. Section 4 presents ourapproach for solving singular fuzzy nonlinear systems. Numerical results are
reported in section 5, and nally conclusion is given in section 6
Numerous authors have proposed di erent approaches to nd the solutionof fuzzy nonlinear systems with fuzzy coecients involving fuzzy variables.Nevertheless, the famous iterative method is Newton's approach. It is im-portant to mention that, [14] presented a Newton's method for solving fuzzynonlinear equations, which was extended to solve dual fuzzy nonlinear systemsby [10]. In the work of [6] the numerical solution of fuzzy nonlinear systems viasteepest descent scheme has been presented. Via midpoint approach on New-ton's method, [16] proposed an iterative method for solving fuzzy nonlinearsystems. Di erent approaches for solving fuzzy nonlinear systems have alsobeen given by many researchers, such as [1], [7] etc. All the existing methodsare based on Newtonian approach. It is remarkable to point out that, themajor weakness of Newton's method arise from the non- singularity of the Ja-cobian matrix in the neighborhood of the solution for successful quadratic rateof convergence [2] . Violating this condition, i.e. the Jacobian to be singularthe convergence is too slow and may even be lost. Based on this fact, Newton's-type method that required Jacobian computation may not be suitable alwaysfor solving singular fuzzy nonlinear equations. This is what motivates us tosuggest a new approach for solving singular fuzzy nonlinear equations. Theanticipation has been to bypass the point at which the Jacobian is singular.The method proposed in this work is computationally cheaper than ClassicalNewton's method. This paper has been arranged as follows; we present briefoverview and some basic de nitions of the fuzzy nonlinear equations in section2, description of Newton's method is given in section 3. Section 4 presents ourapproach for solving singular fuzzy nonlinear systems. Numerical results arereported in section 5, and nally conclusion is given in section 6
การแปล กรุณารอสักครู่..