IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v13y2025i2p250-d1566197.html
   My bibliography  Save this article

A Novel Approximation Method for Solving Ordinary Differential Equations Using the Representation of Ball Curves

Author

Listed:
  • Abdul Hadi Bhatti

    (Department of Mathematics and Applied Sciences, Middle East College, Muscat 124, Oman)

  • Sharmila Karim

    (School of Quantitative Sciences, University Utara Malaysia, Sintok 06010, Kedah, Malaysia)

  • Ala Amourah

    (Mathematics Education Program, Faculty of Education and Arts, Sohar University, Sohar 311, Oman
    Applied Science Research Center, Applied Science Private University, Amman 11937, Jordan)

  • Ali Fareed Jameel

    (Mathematics Education Program, Faculty of Education and Arts, Sohar University, Sohar 311, Oman)

  • Feras Yousef

    (Department of Mathematics, The University of Jordan, Amman 11942, Jordan
    Department of Mathematics, Hampton University, Hampton, VA 23669, USA)

  • Nidal Anakira

    (Mathematics Education Program, Faculty of Education and Arts, Sohar University, Sohar 311, Oman)

Abstract

Numerical methods are frequently developed to investigate concepts for approximately solving ordinary differential equations (ODEs). To achieve minimal error and higher accuracy in approximate solutions, researchers have focused on developing algorithms using various numerical techniques. This study proposes the application of Ball curves, specifically the Said–Ball curve, for estimating solutions to higher-order ODEs. To obtain the best control points of the Said–Ball curve, the least squares method is used. These control points are calculated by minimizing the residual error through the sum of the squares of the residual functions. To demonstrate the proposed method, several boundary value problems are presented, and their performance is compared with existing methods in terms of error accuracy. The numerical results indicate that the proposed method improves error accuracy compared to existing studies, including those employing Bézier curves and the steepest descent method.

Suggested Citation

  • Abdul Hadi Bhatti & Sharmila Karim & Ala Amourah & Ali Fareed Jameel & Feras Yousef & Nidal Anakira, 2025. "A Novel Approximation Method for Solving Ordinary Differential Equations Using the Representation of Ball Curves," Mathematics, MDPI, vol. 13(2), pages 1-25, January.
  • Handle: RePEc:gam:jmathe:v:13:y:2025:i:2:p:250-:d:1566197
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/13/2/250/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-7390/13/2/250/
    Download Restriction: no
    ---><---

    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:gam:jmathe:v:13:y:2025:i:2:p:250-:d:1566197. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.