An Artificial Approach for the Fractional Order Rape and Its Control Model

Wajaree Weera, Zulqurnain Sabir, Muhammad Asif Zahoor Raja, Salem Ben Said, Maria Emilia Camargo, Chantapish Zamart, Thongchai Botmart

Research output: Contribution to journalArticlepeer-review

Abstract

The current investigations provide the solutions of the nonlinear fractional order mathematical rape and its control model using the strength of artificial neural networks (ANNs) along with the Levenberg-Marquardt backpropagation approach (LMBA), i.e., artificial neural networks-LevenbergMarquardt backpropagation approach (ANNs-LMBA). The fractional order investigations have been presented to find more realistic results of the mathematical form of the rape and its control model. The differential mathematical form of the nonlinear fractional order mathematical rape and its control model has six classes: susceptible native girls, infected immature girls, susceptible knowledgeable girls, infected knowledgeable girls, susceptible rapist population and infective rapist population. The rape and its control differential system using three different fractional order values is authenticated to perform the correctness of ANNs-LMBA. The data is used to present the rape and its control differential system is designated as 70% for training, 14% for authorization and 16% for testing. The obtained performances of the ANNs-LMBA are compared with the dataset of the Adams-Bashforth-Moulton scheme. To substantiate the consistency, aptitude, validity, exactness, and capability of the LMBA neural networks, the obtained numerical values are provided using the state transitions (STs), correlation, regression, mean square error (MSE) and error histograms (EHs).

Original languageEnglish
Pages (from-to)3421-3438
Number of pages18
JournalComputers, Materials and Continua
Volume74
Issue number2
DOIs
Publication statusPublished - 2023

Keywords

  • fractional order
  • levenberg-marquardt backpropagation approach
  • neural networks
  • Rape and its control differential system
  • reference solutions

ASJC Scopus subject areas

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

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