A WEB-BASED TOOL FOR GENERATING BLOCK LINEAR MULTISTEP METHODS

Authors

  • Christie Ishola Department of Mathematics, National Open University of Nigeria, University Village, Plot 91 Cadastral Zone, Nnamdi Azikiwe Express Way, Jabi, Abuja FCT, Nigeria Author
  • Oyewole Oyelami Department of Mathematics, National Open University of Nigeria, University Village, Plot 91 Cadastral Zone, Nnamdi Azikiwe Express Way, Jabi, åAbuja FCT, Nigeria Author
  • Collins Elebor Department of Mathematics, National Open University of Nigeria, University Village, Plot 91 Cadastral Zone, Nnamdi Azikiwe Express Way, Jabi, Abuja FCT, Nigeria Author

DOI:

https://doi.org/10.60787/jnamp.vol70no.566

Keywords:

Linear Multistep Methods, Ordinary Differential Equations, Interpolation, Collocation, Web-Based Tool, Numerical Methods

Abstract

Linear Multistep Methods are widely used to obtain numerical solutions of ordinary differential equations. However, generating these methods manually can be computationally challenging, time-consuming, and prone to errors. Existing mathematical software’s lacks the flexibility to efficiently automate the derivation of Linear Multistep Methods. This paper introduces a web-based tool designed to address these limitations by automating the generation of LMMs of first and second derivative methods using interpolation and collocation techniques. The tool enhances computational efficiency, saves time, and simplifies the process of solving ODEs. The backend of the tool is developed in Python using the FASTAPI framework. The frontend, built with React, provides a dynamic and responsive interface for user interaction. This architecture’s integration of Python and React highlights the advantages of combining a powerful computational backend with an intuitive frontend. The effectiveness of the tool is demonstrated by successfully generating well-known Linear Multistep Methods.

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Published

2025-07-21

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How to Cite

A WEB-BASED TOOL FOR GENERATING BLOCK LINEAR MULTISTEP METHODS. (2025). The Journals of the Nigerian Association of Mathematical Physics, 70, 167-178. https://doi.org/10.60787/jnamp.vol70no.566

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