Walsh function-based numerical approach for nonlinear stochastic integral equations: Application to stochastic logistic models

The current research study proposes an efficient numerical method for obtaining an approximate solution to nonlinear stochastic integral equations implementing the collocation method and the Walsh operational matrices. Given the complexity of solving each integral equation exactly, we use a numerical approach that converts the equation into a system of algebraic equations, yielding an approximate solution. Through error analysis, the method is found to exhibit linear convergence, underscoring its efficiency. We offer numerical tests to show the accuracy and usefulness of the proposed approach. This work also demonstrates the applicability of the method to dealing with the stochastic logistic model.

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Publication Details

Journal
Boundary Value Problems
Published
2025-09-26
DOI
https://doi.org/10.1186/s13661-025-02129-0
Citations
1
Primary Topic
Stochastic processes and financial applications
Type
article
Field-Weighted Citation Impact
2.21
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article

Walsh function-based numerical approach for nonlinear stochastic integral equations: Application to stochastic logistic models

Prit Pritam Paikaray, Mohammad Izadi, Nigam Chandra Parida, Sanghamitra Beuria
1 citations
Boundary Value Problems
Stochastic processes and financial applications
2.21
article

Walsh function-based numerical approach for nonlinear stochastic integral equations: Application to stochastic logistic models

Prit Pritam Paikaray, Mohammad Izadi, Nigam Chandra Parida, Sanghamitra Beuria
article en
1 citations

Abstract

The current research study proposes an efficient numerical method for obtaining an approximate solution to nonlinear stochastic integral equations implementing the collocation method and the Walsh operational matrices. Given the complexity of solving each integral equation exactly, we use a numerical approach that converts the equation into a system of algebraic equations, yielding an approximate solution. Through error analysis, the method is found to exhibit linear convergence, underscoring its efficiency. We offer numerical tests to show the accuracy and usefulness of the proposed approach. This work also demonstrates the applicability of the method to dealing with the stochastic logistic model.

Boundary Value ProblemsVol. 2025(1)
Shahid Bahonar University of Kerman (IR), Odisha University of Agriculture and Technology (IN), Indian Institute of Technology Bhubaneswar (IN)
Openalex Percentile: Top 10%
Stochastic processes and financial applications
2.21
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Walsh function-based numerical approach for nonlinear stochastic integral equations: Application to stochastic logistic models — Prit Pritam Paikaray, Mohammad Izadi, et al. · Boundary Value Problems (2025) | TGRS Research Map | TGRS