EXTENDED PREDICTOR-CORRECTOR METHODS FOR SOLVING FUZZY DIFFERENTIAL EQUATIONS UNDER GENERALIZED DIFFERENTIABILITY
Authors
Abstract:
In this paper, the (m+1)-step Adams-Bashforth, Adams-Moulton, and Predictor-Correctormethods are used to solve rst-order linear fuzzy ordinary dierential equations. The conceptsof fuzzy interpolation and generalised strongly dierentiability are used, to obtaingeneral algorithms. Each of these algorithms has advantages over current methods. Moreover,for each algorithm a convergence formula can be obtained . The convergence of thesemethods is proven in detail. Finally, these methods are illustrated using example initial valueproblems.
similar resources
extended predictor-corrector methods for solving fuzzy differential equations under generalized differentiability
in this paper, the (m+1)-step adams-bashforth, adams-moulton, and predictor-correctormethods are used to solve rst-order linear fuzzy ordinary dierential equations. the conceptsof fuzzy interpolation and generalised strongly dierentiability are used, to obtaingeneral algorithms. each of these algorithms has advantages over current methods. moreover,for each algorithm a convergence formula can b...
full textImproved predictor-corrector method for solving fuzzy differential equations under generalized differentiability
In this paper, an improved predictor-corrector methods (IPC) to solve fuzzy differential equation under generalized differentiability are discussed. The methods proposed here are based on generalized characterization theorem. Using the Generalized Characterization we can translate a fuzzy differential equation into two ODE systems. Also, the convergence and stability of the proposed methods are...
full textA Numerical Approach for Solving Forth Order Fuzzy Differential Equations Under Generalized Differentiability
In this paper a numerical method for solving forth order fuzzy dierentialequations under generalized differentiability is proposed. This method is basedon the interpolating a solution by piecewise polynomial of degree 8 in the rangeof solution . We investigate the existence and uniqueness of solutions. Finally anumerical example is presented to illustrate the accuracy of the new technique.
full textGeneralized H-differentiability for solving second order linear fuzzy differential equations
In this paper, a new approach for solving the second order fuzzy differential equations (FDE) with fuzzy initial value, under strongly generalized H-differentiability is presented. Solving first order fuzzy differential equations by extending 1-cut solution of the original problem and solving fuzzy integro-differential equations has been investigated by some authors (see for example cite{darabi...
full textNumerical solution of fuzzy differential equations under generalized differentiability by fuzzy neural network
In this paper, we interpret a fuzzy differential equation by using the strongly generalized differentiability concept. Utilizing the Generalized characterization Theorem. Then a novel hybrid method based on learning algorithm of fuzzy neural network for the solution of differential equation with fuzzy initial value is presented. Here neural network is considered as a part of large eld called ne...
full texta numerical approach for solving forth order fuzzy differential equations under generalized differentiability
in this paper a numerical method for solving forth order fuzzy di erentialequations under generalized differentiability is proposed. this method is basedon the interpolating a solution by piecewise polynomial of degree 8 in the rangeof solution . we investigate the existence and uniqueness of solutions. finally anumerical example is presented to illustrate the accuracy of the new technique.
full textMy Resources
Journal title
volume 5 issue 2 (SPRING)
pages 149- 171
publication date 2015-03-21
By following a journal you will be notified via email when a new issue of this journal is published.
Hosted on Doprax cloud platform doprax.com
copyright © 2015-2023