Neural network approach to intricate problems solving for ordinary differential equations


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Abstract

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.

About the authors

E. M. Budkina

Moscow Aviation Institute

Author for correspondence.
Email: emb0909@rambler.ru
Russian Federation, Moscow

E. B. Kuznetsov

Moscow Aviation Institute

Email: emb0909@rambler.ru
Russian Federation, Moscow

T. V. Lazovskaya

Computer Center of the FEB RAS

Email: emb0909@rambler.ru
Russian Federation, Khabarovsk

D. A. Tarkhov

Peter the Great Saint-Petersburg Politechnical University

Email: emb0909@rambler.ru
Russian Federation, St. Petersburg

T. A. Shemyakina

Peter the Great Saint-Petersburg Politechnical University

Email: emb0909@rambler.ru
Russian Federation, St. Petersburg

A. N. Vasilyev

Peter the Great Saint-Petersburg Politechnical University

Email: emb0909@rambler.ru
Russian Federation, St. Petersburg

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