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Numerical Solution of Blasius Equation through Neural Networks Algorithm

机译:基于神经网络算法的Blasius方程数值解

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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.
机译:在本文中,数学技术已用于解决Blasius微分方程。该方法使用优化的人工神经网络逼近,顺序二次规划算法和AST-INP混合技术。文献中报道的对该问题的数值处理基于射击和有限差分法,而我们的数学方法非常简单。数值测试表明,使用所提出的方法获得的解决方案比文献报道的精度更高。统计分析提供了该模型的收敛性。

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