IDEAS home Printed from https://ideas.repec.org/a/wsi/fracta/v31y2023i06ns0218348x23401485.html
   My bibliography  Save this article

Design Of Bio-Inspired Heuristic Technique Integrated With Sequential Quadratic Programming For Nonlinear Model Of Pine Wilt Disease

Author

Listed:
  • MUHAMMAD SHOAIB

    (Department of Mathematics, COMSATS University, Islamabad, Attock Campus, Pakistan†Yuan Ze University, AI Center, Taoyuan 320, Taiwan)

  • RAFIA TABASSUM

    (Department of Mathematics, COMSATS University, Islamabad, Attock Campus, Pakistan)

  • KOTTAKKARAN SOOPPY NISAR

    (��Department of Mathematics, College of Sciences and Humanities, Prince Sattam Bin AbdulAziz University, Al Kharj 16278, Saudi Arabia)

  • MUHAMMAD ASIF ZAHOOR RAJA

    (�Future Technology Research Center, National Yunlin University of Science and Technology, 123 University Road, Section 3, Douliou, Yunlin 64002, Taiwan)

  • FAROOQ AHMED SHAH

    (Department of Mathematics, COMSATS University, Islamabad, Attock Campus, Pakistan)

  • MOHAMMED S. ALQAHTANI

    (�Radiological Sciences Department, College of Applied Medical Sciences, King Khalid University, Abha 61421, Saudi Arabia∥BioImaging Unit, Space Research Centre, Michael Atiyah Building, University of Leicester, Leicester LE1 7RH, UK)

  • C. AHAMED SALEEL

    (*Department of Mechanical Engineering, College of Engineering, King Khalid University, Asir-Abha 61421, Saudi Arabia)

  • H. M. ALMOHIY

    (�Radiological Sciences Department, College of Applied Medical Sciences, King Khalid University, Abha 61421, Saudi Arabia)

Abstract

This investigation aims to investigate the pine wilt disease model (PWDM) employing hybrid bio-inspired algorithm. The artificial neural networks-based genetic algorithm (ANNs-GA) as global search and sequential quadratic programming (SQP) serve as local search framework. The model consists of two populations, i.e. host (h) and vector (v). There are four classes in host population representing susceptible host (Sh), exposed host (Eh), asymptomatic host (Ah) and infectious host (Ih) whereas in vector susceptible (Sv) and infectious (Iv) class are present. Activation function is introduced for the formulation of the fitness-based function as mean squared error by using nonlinear PWD equations for the accomplishment of ANNs-GASQP paradigm. The stability, robustness and effectiveness of proposed paradigm is comparatively evaluated through Adam numerical scheme with absolute error analysis. Computational complexity of GASQP is determined by convergence criteria of best global weight, fitness evaluation, time, generations, iterations, function counts and mean square error. Moreover, the statistical analysis is performed via Theil’s inequality coefficients (TICs), mean of absolute deviation (MAD) and root mean squared error (RMSE) for multiple trials of ANNs-GASQP. Results reveal that accuracy is obtained up to 3–11 decimal places which proves the reliability of proposed ANNs-GASQP solver.

Suggested Citation

  • Muhammad Shoaib & Rafia Tabassum & Kottakkaran Sooppy Nisar & Muhammad Asif Zahoor Raja & Farooq Ahmed Shah & Mohammed S. Alqahtani & C. Ahamed Saleel & H. M. Almohiy, 2023. "Design Of Bio-Inspired Heuristic Technique Integrated With Sequential Quadratic Programming For Nonlinear Model Of Pine Wilt Disease," FRACTALS (fractals), World Scientific Publishing Co. Pte. Ltd., vol. 31(06), pages 1-20.
    • Handle: RePEc:wsi:fracta:v:31:y:2023:i:06:n:s0218348x23401485
    DOI: 10.1142/S0218348X23401485
    as

    Download full text from publisher

    File URL: http://www.worldscientific.com/doi/abs/10.1142/S0218348X23401485
    Download Restriction: Access to full text is restricted to subscribers
    File URL: https://libkey.io/10.1142/S0218348X23401485?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.

    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:wsi:fracta:v:31:y:2023:i:06:n:s0218348x23401485. 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: Tai Tone Lim (email available below). General contact details of provider: https://www.worldscientific.com/worldscinet/fractals .

    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.