Frequency domain methods for the solutions of N-order fuzzy differential equations

a b s t r a c t This paper presents a novel technique for solving two new form of equation with fuzzy and integrodifferential equations. The proposed numerical iterative technique is based on the use of the reproducing Kernel theory. Two numerical examples are given to show the effectiveness and performance of the proposed technique. Simulation results are illustrated and comparative studies with past published works to the exact solution from Laplace transform of order integer have been performed to emphasize the simplicity and accuracy of the proposed technique. Moreover, future applications of the proposed technique are also discussed. Numerical experimental results fully support the findings of the proposed analytical approaches. Ó 2017 The Authors. Production and hosting by Elsevier B.V. on behalf of King Saud University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

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“…For more details, please refer to Buckley and Qu (1991), Arshad and Lupulescu (2011) and Yue et al (1998).…”

Section: Fuzzy Definitionmentioning

confidence: 99%

“…The Triangular and trapezoidal fuzzy numbers respectively (Yue et al, 1998;Ahmad et al, 2013), are defined as follows:…”

Section: Fuzzy Definitionmentioning

confidence: 99%

New implementation of reproducing kernel Hilbert space method for solving a fuzzy integro-differential equation of integer and fractional orders

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Frequency domain methods for the solutions of N-order fuzzy differential equations

Cited by 11 publications

References 6 publications

New implementation of reproducing kernel Hilbert space method for solving a fuzzy integro-differential equation of integer and fractional orders

New implementation of reproducing kernel Hilbert space method for solving a fuzzy integro-differential equation of integer and fractional orders

A Review of Fuzzy Set Theoretic Approaches and Their Applications in Environmental Practice

Decision Scenario: Problems and Prospects

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