Biomedical Advantages of Magnetohydrodynamics Williamson Nanofluid: Optimization of Multiple Linear Regression and Multilayer Perceptron

The Williamson magnetohydrodynamics (MHD) nanofluids have been connected to real-world situations or practical scenarios in the essential benefits of several fields, such as industrial heat transfer enhancement, electronics for cooling electronics devices, and constructions to improve the efficiency of solar thermal collectors. The highlights of this study are biomedical processes for orthopaedical implant lubrication, bioimaging, drug delivery systems, and hyperthermia therapy for cancer treatment. This study investigates the flow of Williamson nanofluid (WNF) over a porous stretched sheet, including mass and heat transmission. Similarity expulsion adapts partial differential equations to ordinary differential equations and implements the BVP4C innovator from the MATLAB software. These results display that the velocity distribution declined for the Williamson parameter We = 0.01, 0.31, 0.61, 0.91 developed because of a faster flow near the surface. The temperature profile dropped as the maximum value of the Prandtl number Pr = 0.3, 0.7, 1.3, 1.7 describes a squeezing in thermal boundary layer thickness. Improvement of Schmidt number values Sc = 0.2, 0.4, 0.6, 0.8, 0.10 when the reduction of concentration profile indicates complex particle interactions and diffusion, this study examined heat transfer and mass transport attributes such as skin friction, Nusselt number, and Sherwood number. In addition, it customized the precision level of machine learning under multiple linear regression (MLR) by 95%, and a multilayer perceptron (MLP) dealing with the Levenberg-Marquardt backpropagation algorithm engaged the correct data for outstanding results of 99% accurate estimates for exhaustive positions. Finally, verify the precision and integrity of the presented data, including graphs and tables, against previous findings.