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An artificial neural network scheme for the numerical analysis of a Zika virus model with the effect of environmental pollution | ||
| Computational Methods for Differential Equations | ||
| مقالات آماده انتشار، پذیرفته شده، انتشار آنلاین از تاریخ 16 آبان 1405 اصل مقاله (5.41 M) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22034/cmde.2026.66792.3156 | ||
| نویسندگان | ||
| Muhammad Waseem* ؛ Maryam Nusrat | ||
| Department of Mathematics, COMSATS University Islamabad, Vehari Campus, Pakistan. | ||
| چکیده | ||
| The objective of this study is to present numerical computations of a fractional order Zika virus (ZIKV) model by developing a computational framework that incorporates stochastic Levenberg-Marquardt backpropagation neural networks (LMBNNs). In this paper, we present a fractional-order model for the ZIKV with the effect of environmental pollution, utilizing the Caputo fractional derivative. Fractional-order derivatives have been employed to achieve more precise performance of the fractional-order mathematical ZIKV model in comparison to integer-order derivatives. The fractional order ZIKV model is categorized into five classes: susceptible (Sh), stressed (Shs), infected (Ih), susceptible (Sv) and infected (Iv). Four different cases involving fractional order derivatives have been numerically demonstrated using the mathematical ZIKV model. The results obtained from the ZIKV model are displayed by employing the computational stochastic framework of LMBNNs, which involves verification, training, and evaluation procedures aimed at reducing the mean square error (MSE). For the fractional-order mathematical ZIKV model, the data selection process is carried out as follows: 70% for training and 15% for certification and testing. A thorough study has been conducted to examine regression analysis, correlation, MSE, error histograms (EHs), and information about STs in order to evaluate the proficiency and accuracy of the suggested computing framework. The numerical findings shows the validity of the stochastic LMBNNs computing framework. | ||
| کلیدواژه‌ها | ||
| Neural networks scheme؛ Caputo fractional derivative؛ Levenberg-Marquardt backpropagation؛ Zika virus model؛ Numerical simulations | ||
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آمار تعداد مشاهده مقاله: 6 تعداد دریافت فایل اصل مقاله: 4 |
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