numerical solution of fuzzy initial value problems under generalized dierentiability by hpm

Numerical solution of fuzzy initial value problems under generalized dierentiability by HPM

numerical solution of fuzzy initial value problems under generalized dierentiability by hpm

solution of the rst order fuzzy dierential equations with generalized dierentiability

in this paper, we study rst order linear fuzzy dierential equations with fuzzy coecient and initial value. we use the generalized dierentiability concept and apply the exponent matrix to present the general form of their solutions. finally, one example is given to illustrate our results.

Numerical 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...

Numerical Methods for Fuzzy Initial Value Problems

In this paper, fuzzy initial value problems for modelling aspects of uncertainty in dynam­ ical systems are introduced and interpreted from a probabilistic point ofview. Due to the uncertainty incorporated in the model, the behavior of dynamical systems modelIed in this way will generally not be unique. Rather, we obtain a large set of trajectories which are more or less compatible with the des...

Implicit One-step L-stable Generalized Hybrid Methods for the Numerical Solution of First Order Initial Value problems

In this paper, we introduce the new class of implicit L-stable generalized hybrid methods for the numerical solution of first order initial value problems. We generalize the hybrid methods with utilize ynv directly in the right hand side of classical hybrid methods. The numerical experimentation showed that our method is considerably more efficient compared to well known methods used for the n...