A numerical treatment through Bayesian regularization neural network for the chickenpox disease model.

Journal: Computers in biology and medicine
PMID: 39923585

Abstract

OBJECTIVES: The current research investigations designates the numerical solutions of the chickenpox disease model by applying a proficient optimization framework based on the artificial neural network. The mathematical form of the chickenpox disease model is divided into different categories of individuals, susceptible, vaccinated, infected, exposed, recovered, and infected with/without complications.

Authors

  • Zulqurnain Sabir
    Department of Mathematics and Statistics, Hazara University, Mansehra, Pakistan.
  • Muhammad Athar Mehmood
    Department of Mathematics, University of Gujrat, Pakistan. Electronic address: muhammadatharmehmood@gmail.com.
  • Muhammad Umar
    Department of Mathematics and Statistics, Hazara University, Mansehra, Pakistan.
  • Soheil Salahshour
    Faculty of Engineering and Natural Sciences, Istanbul Okan University, Istanbul, Turkey; Faculty of Engineering and Natural Sciences, Bahcesehir University, Istanbul, Turkey; Department of Computer Science and Mathematics, Lebanese American University, Beirut, Lebanon.
  • Yener Altun
    Faculty of Economics and Administrative Sciences, Department of Business Administration, Yuzuncu Yil University, Van, Turkey. Electronic address: yeneraltun@yyu.edu.tr.
  • Adnène Arbi
    Department of LIM (LR01ES13), EPT, University of Carthage, Carthage, Tunisia. Electronic address: adnen.arbi@enseignant.edunet.tn.
  • Mohamed R Ali
    Faculty of Engineering and Technology, Future University, Cairo, Egypt.

Keywords

External Resources

Popular Topics
Recent Journals