Exponential Spline Method for Solving Fuzzy Integro-Differential Equations

Authors

  • Fatima K. Dawood
  • Rokan Khaji

DOI:

https://doi.org/10.24237/ASJ.02.03.768B

Keywords:

Fuzzy integro-differential equations, Exponential Spline, Exact solution, Approximate solution, Fuzzy parameter.

Abstract

In this paper, we consider a new class of fuzzy functions called Fuzzy Integro- Differential Equations.Some numerical methods, such as cubic spline have been used to determine the solutions of these equations. We extend these numerical techniques to find the optimal solutions. Exponential spline technique is used for this. The results shown that Exponential spline method is more accurate in terms of absolute error.  Based on the parametric form of the fuzzy number, the integro- differential equation is contacted into two systems of the second kind. Illustrative examples are given to demonstrate the high precision and good performance of the new class. Graphical representations reveal the symmetry between lower and upper cut represent of fuzzy solutions and may be helpful for a better understanding of fuzzy model artificial, intelligence, medical science and quantum. 

References

C. E. Shanon, A mathematical Theory of Communication, Bell systems technology, 27, 379-423, 623-656(1948)

S. Seikkala, On the fuzzy initial value problem. Fuzzy sets and systems, 24(3), 319-330(1987)

D. Dubois, H. Prade, Towards fuzzy differential calculus part 1: Integration of fuzzy mappings. Fuzzy sets and Systems, 8(1), 1-17(1982)

O. Kaleva, The Cauchy problem for fuzzy differential equations. Fuzzy sets and systems, 35(3), 389-396(1990)

S. Hajighasemi, T. Allahviranloo, M. Khezerloo, M. Khorasany, S. Salahshour, Existence and uniqueness of solutions of fuzzy Volterra integro-differential equations, In: Information Processing and Management of Uncertainty in Knowledge-Based Systems. Applications: 13th International Conference, IPMU 2010, Dortmund, Germany, June 28–July 2, Proceedings, Part II 13 pp, 491-500, Springer Berlin Heidelberg(2010)

F. Ishak, N. Chaini, Numerical computation for solving fuzzy differential equations, Indonesian Journal of Electrical Engineering and Computer Science, 16(2), 1026-1033(2019)

S. S. Chang, L. A. Zadeh, On fuzzy mapping and control. IEEE Transactions on Systems, Man, and Cybernetics, (1), 30-34(1972)

R. Jr Goetschel, W. Voxman, Fuzzy circuits. Fuzzy Sets and Systems, 32(1), 35-43(1989)

Y. Chalco-Cano, H. Roman-Flores, on new solutions of fuzzy differential equations, Chaos, Solitons & Fractals, 38(1), 112-119(2008)

R. Bello, R. Falcon, J. L. Verdegay, (Eds.). Uncertainty management with fuzzy and rough sets, (Recent advances and applications, 2019), 127- 139

D. Dubois, H. Prade, (Eds.)., Fundamentals of fuzzy sets, Vol. 7, (Springer Science & Business Media, 2012) ‏

P. Darabi, S. Moloudzadeh, H. Khandani, A numerical method for solving first-order fully fuzzy differential equation under strongly generalized H-differentiability, Soft Computing, 20, 4085-4098 (2016)

S. Karpagappriya, N. Alessa, P. Jayaraman, K. Loganathan, A Novel Approach for Solving Fuzzy Differential Equations Using Cubic Spline Method, Mathematical Problems in Engineering, 1-9(2021)

N. N. Hasan, D. A. Hussien, Generalized Spline method for integro-differential equations of fractional order, Iraqi Journal of Science, 1093-1099(2018)‏

M. Zeinali, Approximate solution of fuzzy Hammerstein integral equation by using fuzzy B-spline series, Sohag Journal of Mathematics, 4, 19-25(2017)

Downloads

Published

2024-07-01

How to Cite

Fatima K. Dawood, & Rokan Khaji. (2024). Exponential Spline Method for Solving Fuzzy Integro-Differential Equations . Academic Science Journal, 2(3), 54–65. https://doi.org/10.24237/ASJ.02.03.768B

Issue

Section

Articles