IDEAS home Printed from https://ideas.repec.org/a/eee/apmaco/v371y2020ics0096300319309397.html
   My bibliography  Save this article

An iterative algorithm for solving two dimensional nonlinear stochastic integral equations: A combined successive approximations method with bilinear spline interpolation

Author

Listed:
  • Alipour, Sahar
  • Mirzaee, Farshid

Abstract

The authors propose a numerical iterative algorithm based on a combination of the successive approximations method and the bilinear spline interpolation. This algorithm is used to obtain an approximate solution of two-dimensional nonlinear stochastic Ito^-Volterra integral equation. In fact, this algorithm is an attractive extension of the numerical iterative approach for a class of two-dimensional nonlinear stochastic Itô-Volterra integral equations. To reach this aim, the bilinear spline interpolation, Gauss-Legendre quadrature formulas for double integrals and two dimensional Ito^ approximation are presented. The effectiveness of the method is shown for three examples. The obtained results and the convergence analysis theorems reveal that the suggested algorithm is very efficient and the convergence rate is O(h2).

Suggested Citation

  • Alipour, Sahar & Mirzaee, Farshid, 2020. "An iterative algorithm for solving two dimensional nonlinear stochastic integral equations: A combined successive approximations method with bilinear spline interpolation," Applied Mathematics and Computation, Elsevier, vol. 371(C).
  • Handle: RePEc:eee:apmaco:v:371:y:2020:i:c:s0096300319309397
    DOI: 10.1016/j.amc.2019.124947
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0096300319309397
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.amc.2019.124947?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Dareiotis, Konstantinos & Leahy, James-Michael, 2016. "Finite difference schemes for linear stochastic integro-differential equations," Stochastic Processes and their Applications, Elsevier, vol. 126(10), pages 3202-3234.
    2. Mei, Hongwei & Yin, George & Wu, Fuke, 2016. "Properties of stochastic integro-differential equations with infinite delay: Regularity, ergodicity, weak sense Fokker–Planck equations," Stochastic Processes and their Applications, Elsevier, vol. 126(10), pages 3102-3123.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Solhi, Erfan & Mirzaee, Farshid & Naserifar, Shiva, 2023. "Approximate solution of two dimensional linear and nonlinear stochastic Itô–Volterra integral equations via meshless scheme," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 207(C), pages 369-387.
    2. María Isabel Berenguer & Manuel Ruiz Galán, 2022. "An Iterative Algorithm for Approximating the Fixed Point of a Contractive Affine Operator," Mathematics, MDPI, vol. 10(7), pages 1-10, March.
    3. Ahmadinia, M. & Afshariarjmand, H. & Salehi, M., 2023. "Numerical solution of multi-dimensional Itô Volterra integral equations by the second kind Chebyshev wavelets and parallel computing process," Applied Mathematics and Computation, Elsevier, vol. 450(C).
    4. Zhang, Zhiguo & Kon, Mark A., 2022. "Wavelet matrix operations and quantum transforms," Applied Mathematics and Computation, Elsevier, vol. 428(C).
    5. Wen, Xiaoxia & Huang, Jin, 2021. "A combination method for numerical solution of the nonlinear stochastic Itô-Volterra integral equation," Applied Mathematics and Computation, Elsevier, vol. 407(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.

      Corrections

      All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:apmaco:v:371:y:2020:i:c:s0096300319309397. See general information about how to correct material in RePEc.

      If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

      If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

      If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

      For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/applied-mathematics-and-computation .

      Please note that corrections may take a couple of weeks to filter through the various RePEc services.

      IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.