首页|Findings from Department of Mathematics Provide New Insights into Nanofluids (En tropy Generation Analysis of Microrotating Casson’s Nanofluid With Darcy-forchhe imer Porous Media Using a Neural Computing Based On Levenberg-marquardt Algorith m)
Findings from Department of Mathematics Provide New Insights into Nanofluids (En tropy Generation Analysis of Microrotating Casson’s Nanofluid With Darcy-forchhe imer Porous Media Using a Neural Computing Based On Levenberg-marquardt Algorith m)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Research findings on Nanotechnology - Nanofluids are discussed in a new report. According to news reporting out of Sirsa, India, by NewsRx editors, research stated, “PurposeThe purpose of this paper is to show case the utilization of the magnetohydrodynamics-microrotating Casson’s nanoflui d flow model (MHD-MRCNFM) in examining the impact of an inclined magnetic field within a porous medium on a nonlinear stretching plate. This investigation is co nducted by using neural networking techniques, specifically using neural network s-backpropagated with the Levenberg-Marquardt scheme (NNBLMS). Design/methodolog y/approachThe initial nonlinear coupled PDEs system that represented the MRCNFM is transformed into an analogous nonlinear ODEs system by the adoption of simila rity variables.”
SirsaIndiaAsiaAlgorithmsEmerging TechnologiesLevenberg-Marquardt AlgorithmMachine LearningNanofluidsNano technologyNeural ComputingDepartment of Mathematics
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