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In this paper mathematical techniques have been used for the solution ofBlasius differential equation.
The method uses optimized artificial neuralnetworks approximation with Sequential Quadratic Programming algorithm andhybrid AST-INP techniques.
Numerical treatment of this problem reported in theliterature is based on Shooting and Finite Differences Method, while our mathematicalapproach is very simple.
Numerical testing showed that solutions obtained by usingthe proposed methods are better in accuracy than those reported in literature.Statistical analysis provided the convergence of the proposed model.


KEYWORDS

Blasius Equation, Neural Networks, Log-Sigmoid Function, Boundary Value Problems

Cite this paper

Ahmad, I.
and Bilal, M.
2014 Numerical Solution of Blasius Equation through Neural Networks Algorithm.
American Journal of Computational Mathematics, 4, 223-232.
doi: 10.4236-ajcm.2014.43019.






Autor: Iftikhar Ahmad, Muhammad Bilal

Fuente: http://www.scirp.org/





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