Unsupervised neural network model optimized with evolutionary computations for solving variants of nonlinear MHD Jeffery-Hamel problem

A heuristic technique is developed for a nonlinear magnetohydrodynamics （MHD） Jeffery-Hamel problem with the help of the feed-forward artificial neural net- work （ANN） optimized with the genetic algorithm （GA） and the sequential quadratic programming （SQP） method. The twodimensional （2D） MHD Jeffery...

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Veröffentlicht in:	Applied mathematics and mechanics 2015-12, Vol.36 (12), p.1611-1638
Hauptverfasser:	Raja, M. A. Z., Samar, R., Haroon, T., Shah, S. M.
Format:	Artikel
Sprache:	eng
Schlagworte:	algorithm（CA））nonlinear Applications of Mathematics Boundary value problems Classical Mechanics differential equation（ODE） Fluid- and Aerodynamics genetic Genetic algorithms hybrid Jeffery-Hamel Learning theory Magnetohydrodynamics Mathematical analysis Mathematical Modeling and Industrial Mathematics Mathematical models Mathematics Mathematics and Statistics MHD network neural Neural networks ordinary Partial Differential Equations problem programming quadratic sequential technique
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