Designing a novel radial basis neural structure for solving the dynamical hepatitis C virus model
Sabir Z. Yessengaliyev A. Temirzhan A. Koyunbakan H. Bhatti S. Nicolas R.
December 2026Nature Research
Scientific Reports
2026#16Issue 1
The purpose of the current investigation is to design a novel radial basis neural network for solving the dynamical hepatitis C virus model in patients with a high baseline viral load, which represents the nonlinear dynamical structure. The infection and treatment in the hepatitis C virus comprise uninfected hepatocytes, creatively infected hepatocytes, and viruses. The aim of this study is to solve the dynamical hepatitis C virus model in patients with a high baseline viral load with the optimization of the Bayesian regularization scheme. A database reference solution is achieved by the explicit Runge–Kutta in interval 0 and 1 with the step size of 0.01 by data division into training as 72%, while 14%, 14% for endorsement, and testing. Twenty numbers of neurons, a feed forward neural network, activation radial basis function, and the optimization Bayesian regularization approach have been used to solve the hepatitis C virus model. The precision of the scheme is perceived by the outcomes overlapping and the reducible absolute error values, which are found as 10–06 to 10–08. A statistical evaluation utilizing various operators and proportional approaches is carried out in order to assess the solver’s efficiency.
Bayesian regularization , Hepatitis C virus , Numerical outputs , Optimization , Radial basis
Text of the article Перейти на текст статьи
Department of Computer Science and Mathematics, Lebanese American University, Beirut, Lebanon
Department of Computer Science, L.N. Gumilyov Eurasian National University, Astana, Kazakhstan
Department of Mathematics, Faculty of Science, Firat University, Elazig, Turkey
Department of Mathematics, COMSATS University, Abbotabad Campus, Islamabad, Pakistan
Department of Physicall Sciences, Lebanese American University, Beirut, Lebanon
Department of Computer Science and Mathematics
Department of Computer Science
Department of Mathematics
Department of Mathematics
Department of Physicall Sciences
10 лет помогаем публиковать статьи Международный издатель
Книга Публикация научной статьи Волощук 2026 Book Publication of a scientific article 2026