Neural network approach to intricate problems solving for ordinary differential equations
- Авторы: 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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Учреждения:
- Moscow Aviation Institute
- Computer Center of the FEB RAS
- Peter the Great Saint-Petersburg Politechnical University
- Выпуск: Том 26, № 2 (2017)
- Страницы: 96-109
- Раздел: Article
- URL: https://journals.rcsi.science/1060-992X/article/view/194960
- DOI: https://doi.org/10.3103/S1060992X17020011
- ID: 194960
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Аннотация
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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Об авторах
E. Budkina
Moscow Aviation Institute
Автор, ответственный за переписку.
Email: emb0909@rambler.ru
Россия, Moscow
E. Kuznetsov
Moscow Aviation Institute
Email: emb0909@rambler.ru
Россия, Moscow
T. Lazovskaya
Computer Center of the FEB RAS
Email: emb0909@rambler.ru
Россия, Khabarovsk
D. Tarkhov
Peter the Great Saint-Petersburg Politechnical University
Email: emb0909@rambler.ru
Россия, St. Petersburg
T. Shemyakina
Peter the Great Saint-Petersburg Politechnical University
Email: emb0909@rambler.ru
Россия, St. Petersburg
A. Vasilyev
Peter the Great Saint-Petersburg Politechnical University
Email: emb0909@rambler.ru
Россия, St. Petersburg
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