Skip to main content
Log in

Enhanced moving least squares method for solving the stochastic fractional Volterra integro-differential equations of Hammerstein type

  • Original Paper
  • Published:
Numerical Algorithms Aims and scope Submit manuscript

Abstract

One of the challenging and practical issues that have recently attracted the attention of researchers is stochastic equations. One of the important categories in stochastic equations is the stochastic fractional integro-differential equations (SFIDEs), which are practical tools for modeling many phenomena. In this study, we aim to derive a novel numerical method based on the meshless enhanced moving least squares (EMLS) and spectral method for solving SFIDEs, which transform the intended problem to a nonlinear system of algebraic equations. Thus, the complexity of solving the mentioned problem is reduced significantly. Also, we give an error estimate which will be useful in estimating the error of approximate solutions for the problems that we do not have information about their exact solutions. Illustrative numerical examples are also given to clarify the performance and accuracy of the new method. This method is far from computational complexity compared to other methods. Also, obtaining acceptable accuracy by choosing a small number of interpolation nodes and basis functions is one of the innovations of this work.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

Data availability

Data sharing is not applicable to this article as no datasets were generated or analyzed during the current study.

References

  1. Mirzaee, F., Alipour, S.: Cubic B-spline approximation for linear stochastic integro-differential equation of fractional order. J. Comput. Appl. Math. 366, 112440 (2020)

    Article  MathSciNet  Google Scholar 

  2. Mirzaee, F., Solhi, E., Samadyar, N.: Moving least squares and spectral collocation method to approximate the solution of stochastic Volterra-Fredholm integral equations. Appl. Numer. Math. 161, 275–285 (2021)

    Article  MathSciNet  Google Scholar 

  3. Mirzaee, F., Solhi, E., Naserifar, S.: Approximate solution of stochastic Volterra integro-differential equations by using moving least squares scheme and spectral collocation method. Appl. Math. Comput. 10, 126447 (2021)

    MathSciNet  Google Scholar 

  4. Mirzaee, F., Alipour, S., Samadyar, N.: Numerical solution based on hybrid of block-pulse and parabolic functions for solving a system of nonlinear stochastic Itô-Volterra integral equations of fractional order. J. Comput. Appl. Math. 349, 157–171 (2019)

    Article  MathSciNet  Google Scholar 

  5. Fallahpour, M., Khodabin, M., Maleknejad, K.: Approximation solution of two-dimensional linear stochastic Volterra-Fredholm integral equation via two-dimensional Block-pulse functions. Int. J. Ind. Math. 8(4), 423–430 (2016)

    Google Scholar 

  6. Mirzaee, F., Samadyar, N., Hosseini, S.F.: A new scheme for solving nonlinear Stratonovich Volterra integral equations via Bernoulli’s approximation. Appl. Anal. 96(13), 2163–2179 (2017)

    Article  MathSciNet  Google Scholar 

  7. Heydari, M.H., Mahmoudi, M.R., Shakiba, A., Avazzadeh, Z.: Chebyshev cardinal wavelets and their application in solving nonlinear stochastic differential equations with fractional Brownian motion. Commun. Nonlinear Sci. Numer. Simul. 64, 98–121 (2018)

    Article  ADS  MathSciNet  Google Scholar 

  8. Singh, P.K., Saha Ray, S.: An efficient numerical method based on Lucas polynomials to solve multi-dimensional stochastic Itô-Volterra integral equations. Math. Comput. Simul. 203, 826–845 (2023)

    Article  Google Scholar 

  9. Singh, P.K., Saha Ray, S.: Shifted Chebyshev spectral Galerkin method to solve stochastic Itô-Volterra integral equations driven by fractional Brownian motion appearing in mathematical physics. J. Comput. Appl. Math. 42(3), 120 (2023)

    Google Scholar 

  10. Singh, P.K., Saha Ray, S.: A novel study based on shifted Jacobi polynomials to find the numerical solutions of nonlinear stochastic differential equations driven by fractional Brownian motion. Comput. Methods Appl. Math. 23(3), 715–728 (2023)

    Article  MathSciNet  Google Scholar 

  11. Mirzaee, F., Samadyar, N.: On the numerical solution of fractional stochastic integro-differential equations via meshless discrete collocation method based on radial basis functions. Eng. Anal. Bound. Elem. 100, 246–255 (2019)

    Article  MathSciNet  Google Scholar 

  12. Asgari, M.: Block pulse approximation of fractional stochastic integro-differential equation. Commun. Numer. Anal. 2014, 1–7 (2014)

    Article  MathSciNet  Google Scholar 

  13. Taheri, Z., Javadi, S., Babolian, E.: Numerical solution of stochastic fractional integro-differential equation by the spectral collocation method. J. Comput. Appl. Math. 321, 336–347 (2017)

    Article  MathSciNet  Google Scholar 

  14. Singh, A.K., Mehra, M.: Wavelet collocation method based on Legendre polynomials and its application in solving the stochastic fractional integro-differential equations. J. Comput. Sci. 51, 101342 (2021)

    Article  MathSciNet  Google Scholar 

  15. Sayevand, K., Machado, J.T., Masti, I.: On dual Bernstein polynomials and stochastic fractional integro-differential equations. Math. Methods Appl. Sci. 43(17), 9928–9947 (2020)

    Article  ADS  MathSciNet  Google Scholar 

  16. Aryani, E., Babaei, A., Valinejad, A.: A numerical technique for solving nonlinear fractional stochastic integro-differential equations with n-dimensional Wiener process. Comput. Methods Differ. Equ. 10(1), 61–76 (2022)

    MathSciNet  Google Scholar 

  17. Badr, A.A., El-Hoety, H.S.: Monte-Carlo Galerkin approximation of fractional stochastic integro-differential equation. Math. Probl. Eng. 2012, 709106 (2012)

    Article  MathSciNet  Google Scholar 

  18. Mirzaei, D., Schaback, R., Dehghan, M.: On generalized moving least squares and diffuse derivatives. IMA J. Numer. Anal. 32, 923–1000 (2012)

    Article  MathSciNet  Google Scholar 

  19. Shepard, D.: A two-dimensional interpolation function for irregularly spaced points, Proc. 23rd Nat. Conf. ACM Press New York 517–524 (1968)

  20. Lancaster, P., Salkauskas, K.: Surfaces generated by moving least squares methods. Math. Comp. 37, 141–159 (1981)

    Article  MathSciNet  Google Scholar 

  21. Farwig, R.: Multivariate interpolation of arbitrarily spaced data by moving least square methods. J. of Comp. and App. Math. 16, 79–93 (1986)

    Article  MathSciNet  Google Scholar 

  22. Taiwo, O.A., Etuk, M.O., Nwaeze, E., Ogunniran, M.O.: Enhanced moving least square method for the solution of volterra integro-diferential equation: an interpolating polynomial. J. Egypt. Math. Soc. 30(3) (2022)

  23. Zuppa, C.: Error estimates for moving least square approximations. Bull. Braz. Math. Soc. 34(2), 231–249 (2003)

    Article  MathSciNet  Google Scholar 

  24. Assari, P., Adibi, H., Dehghan, M.: A meshless method based on the moving least squares (MLS) approximation for the numerical solution of two-dimensional nonlinear integral equations of the second kind on non-rectangular domains. Numer. Alg. 67(2), 423–455 (2014)

    Article  MathSciNet  Google Scholar 

  25. Wendland, H.: Local polynomial reproduction and moving least squares approximation. IMA J. Numer. Anal. 21(1), 285–300 (2001)

    Article  MathSciNet  Google Scholar 

  26. Oksendal, B.: Stochastic differential equations: an introduction with applications, 5th edn. Springer-Verlag, New York (1998)

    Book  Google Scholar 

  27. Durrett, R.: Stochastic calculus: a practical introduction, CRC press, 2018

  28. Da Prato, G., Zabczyk, J.: Stochastic equations in infinite dimensions, Cambridge University Press, 2014

  29. Blömker, D., Jentzen, A.: Galerkin approximations for the stochastic burgers equation. SIAM J. Numer. Anal. 51(1), 694–715 (2013)

    Article  MathSciNet  Google Scholar 

Download references

Acknowledgements

The authors would like to express our very great appreciation to the editor and anonymous reviewers for their valuable comments and constructive suggestions which have helped to improve the quality and presentation of this paper

Funding

This research received no external funding

Author information

Authors and Affiliations

Authors

Contributions

Conceptualization, Farshid Mirzaee and Erfan Solhi; formal analysis, Erfan Solhi and Shiva Naserifar; investigation, Erfan Solhi and Farshid Mirzaee; methodology, Erfan Solhi and Shiva Naserifar; validation, Erfan Solhi and Farshid Mirzaee; visualization, Erfan Solhi and Farshid Mirzaee; writing—original draft, Erfan Solhi and Shiva Naserifar.

Corresponding author

Correspondence to Farshid Mirzaee.

Ethics declarations

Ethical approval

The authors are consent to participate and consent to publish of this manuscript.

Conflict of interest

All authors declare that they have no conflicts of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Solhi, E., Mirzaee, F. & Naserifar, S. Enhanced moving least squares method for solving the stochastic fractional Volterra integro-differential equations of Hammerstein type. Numer Algor 95, 1921–1951 (2024). https://doi.org/10.1007/s11075-023-01633-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11075-023-01633-7

Keywords

Mathematics Subject Classification (2010)

Navigation