Neural network approach to intricate problems solving for ordinary differential equations
- Autores: Budkina E.M.1, Kuznetsov E.B.1, Lazovskaya T.V.2, Tarkhov D.A.3, Shemyakina T.A.3, Vasilyev A.N.3
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Afiliações:
- Moscow Aviation Institute
- Computer Center of the FEB RAS
- Peter the Great Saint-Petersburg Politechnical University
- Edição: Volume 26, Nº 2 (2017)
- Páginas: 96-109
- Seção: Article
- URL: https://journals.rcsi.science/1060-992X/article/view/194960
- DOI: https://doi.org/10.3103/S1060992X17020011
- ID: 194960
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Resumo
We consider the problems arising in the construction of the solutions of singularly perturbed differential equations. Usually, the decision of such problems by standard methods encounters significant difficulties of various kinds. The use of a common neural network approach is demonstrated in three model problems for ordinary differential equations. The conducted computational experiments confirm the effectiveness of this approach.
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Sobre autores
E. Budkina
Moscow Aviation Institute
Autor responsável pela correspondência
Email: emb0909@rambler.ru
Rússia, Moscow
E. Kuznetsov
Moscow Aviation Institute
Email: emb0909@rambler.ru
Rússia, Moscow
T. Lazovskaya
Computer Center of the FEB RAS
Email: emb0909@rambler.ru
Rússia, Khabarovsk
D. Tarkhov
Peter the Great Saint-Petersburg Politechnical University
Email: emb0909@rambler.ru
Rússia, St. Petersburg
T. Shemyakina
Peter the Great Saint-Petersburg Politechnical University
Email: emb0909@rambler.ru
Rússia, St. Petersburg
A. Vasilyev
Peter the Great Saint-Petersburg Politechnical University
Email: emb0909@rambler.ru
Rússia, St. Petersburg
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