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Neural Computing and Applications

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21.06.2016 | Original Article

Stochastic numerical treatment for solving Falkner–Skan equations using feedforward neural networks

verfasst von: Iftikhar Ahmad, Siraj-ul-Islam Ahmad, Muhammad Bilal, Nabeela Anwar

Erschienen in: Neural Computing and Applications | Sonderheft 1/2017

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Abstract

In this article, the artificial intelligence techniques have been used for the solution of Falkner–Skan (FS) equations based on neural networks optimized with three methods including active set technique, sequential quadratic programming and genetic algorithms (GA) hybridization. Log-sigmoid activation function is used in artificial neural network architecture. The proposed techniques are applied to a number of cases for Falkner–Skan problems, and results were compared with GA hybrid results in all cases and were found accurate. The level of accuracy is examined through statistical analyses based on a sufficiently large number of independent runs.

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Titel: Stochastic numerical treatment for solving Falkner–Skan equations using feedforward neural networks
verfasst von: Iftikhar Ahmad
Siraj-ul-Islam Ahmad
Muhammad Bilal
Nabeela Anwar
Publikationsdatum: 21.06.2016
Verlag: Springer London
Erschienen in: Neural Computing and Applications / Ausgabe Sonderheft 1/2017
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI: https://doi.org/10.1007/s00521-016-2427-0

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