TITLE:
Numerical Solution of Blasius Equation through Neural Networks Algorithm
AUTHORS:
Iftikhar Ahmad, Muhammad Bilal
KEYWORDS:
Blasius Equation, Neural Networks, Log-Sigmoid Function, Boundary Value Problems
JOURNAL NAME:
American Journal of Computational Mathematics,
Vol.4 No.3,
June
24,
2014
ABSTRACT: In this paper mathematical techniques have been used for the solution of
Blasius differential equation. The method uses optimized artificial neural
networks approximation with Sequential Quadratic Programming algorithm and
hybrid AST-INP techniques. Numerical treatment of this problem reported in the
literature is based on Shooting and Finite Differences Method, while our mathematical
approach is very simple. Numerical testing showed that solutions obtained by using
the proposed methods are better in accuracy than those reported in literature.
Statistical analysis provided the convergence of the proposed model.