Numerical Solution for Nonlinear MHD Jeffery-Hamel Blood Flow Problem through Neural Networks Optimized Techniques
نویسندگان
چکیده
The purpose of study is to develop numerical techniques for nonlinear magnetohydrodynamics (MHD) JefferyHamel blood flow problem to analyze the behavior of blood flow and its contribution in high blood pressure through artificial neural networks trained with Active Set and Interior Point Algorithm. First we transform three-dimensional flow problem into two-dimensional MHD Jeffery-Hamel flow problem, which is converted into an equivalent third order nonlinear ordinary differential equation. These neural network models using log-sigmoid activation function are developed for new transformed equation. Detailed statistical analysis is also included to ensure the reliability and accuracy of the proposed methods through large number of independent runs. Further, comparative studies of the proposed solutions with standard numerical results are presented.
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