This paper presents a numerical method for solving fuzzy delay nonlinear Volterra-Hammerstein integral equations using Legendre wavelets. The importance of this class of equations is highlighted by their application to modeling epidemic problems, which represent a special case. After introducing preliminary definitions related to fuzzy equations and the basic characteristics of Legendre wavelets, we present the parametric form of nonlinear fuzzy delay Volterra-Hammerstein integral equations, which are essentially a system of nonlinear delay integral equations in a non-fuzzy state. We then employ Legendre wavelets, the collocation method, and the Gauss-Legendre quadrature rule to transform the integral equation into a system of algebraic equations that can be solved. Furthermore, we provide a detailed convergence analysis of the proposed method. The accuracy of the method is demonstrated through several numerical examples, with results compared to those obtained using Bernoulli and B-spline wavelet methods. These comparisons confirm the accuracy and efficiency of the presented method.
Bisheh Niasar, M. (2025). Numerical solution of nonlinear fuzzy Volterra-Hammerstein delay integral equations by using Legendre wavelets. Soft Computing Journal, (), -. doi: 10.22052/scj.2025.255504.1270
MLA
Bisheh Niasar, M. . "Numerical solution of nonlinear fuzzy Volterra-Hammerstein delay integral equations by using Legendre wavelets", Soft Computing Journal, , , 2025, -. doi: 10.22052/scj.2025.255504.1270
HARVARD
Bisheh Niasar, M. (2025). 'Numerical solution of nonlinear fuzzy Volterra-Hammerstein delay integral equations by using Legendre wavelets', Soft Computing Journal, (), pp. -. doi: 10.22052/scj.2025.255504.1270
CHICAGO
M. Bisheh Niasar, "Numerical solution of nonlinear fuzzy Volterra-Hammerstein delay integral equations by using Legendre wavelets," Soft Computing Journal, (2025): -, doi: 10.22052/scj.2025.255504.1270
VANCOUVER
Bisheh Niasar, M. Numerical solution of nonlinear fuzzy Volterra-Hammerstein delay integral equations by using Legendre wavelets. Soft Computing Journal, 2025; (): -. doi: 10.22052/scj.2025.255504.1270