Fractional Order Nonlinear Bone Remodeling Dynamics Using the Supervised Neural Network

Narongsak Yotha, Qusain Hiader, Zulqurnain Sabir, Muhammad Asif Zahoor Raja, Salem Ben Said, Qasem Al-Mdallal, Thongchai Botmart, Wajaree Weera

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

This study aims to solve the nonlinear fractional-order mathematical model (FOMM) by using the normal and dysregulated bone remodeling of the myeloma bone disease (MBD). For the more precise performance of the model, fractional-order derivatives have been used to solve the disease model numerically. The FOMM is preliminarily designed to focus on the critical interactions between bone resorption or osteoclasts (OC) and bone formation or osteoblasts (OB). The connections of OC and OB are represented by a nonlinear differential system based on the cellular components, which depict stable fluctuation in the usual bone case and unstable fluctuation through the MBD. Untreated myeloma causes by increasing the OC and reducing the osteoblasts, resulting in net bone waste the tumor growth. The solutions of the FOMM will be provided by using the stochastic framework based on the Levenberg-Marquardt backpropagation (LVMBP) neural networks (NN), i.e., LVMBPNN. The mathematical performances of three variations of the fractional-order derivative based on the nonlinear disease model using the LVMPNN. The static structural performances are 82% for investigation and 9% for both learning and certification. The performances of the LVMBPNN are authenticated by using the results of the Adams-Bashforth-Moulton mechanism. To accomplish the capability, steadiness, accuracy, and ability of the LVMBPNN, the performances of the error histograms (EHs), mean square error (MSE), recurrence, and state transitions (STs) will be provided.

Original languageEnglish
Pages (from-to)2415-2430
Number of pages16
JournalComputers, Materials and Continua
Volume74
Issue number2
DOIs
Publication statusPublished - 2023

Keywords

  • Bone remodeling
  • artificial neural networks
  • fractional-order
  • levenberg-marquardt backpropagation
  • myeloma disease
  • population cell dynamics

ASJC Scopus subject areas

  • Biomaterials
  • Modelling and Simulation
  • Mechanics of Materials
  • Computer Science Applications
  • Electrical and Electronic Engineering

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