Neural network approach to intricate problems solving for ordinary differential equations


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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.

作者简介

E. Budkina

Moscow Aviation Institute

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Email: emb0909@rambler.ru
俄罗斯联邦, Moscow

E. Kuznetsov

Moscow Aviation Institute

Email: emb0909@rambler.ru
俄罗斯联邦, Moscow

T. Lazovskaya

Computer Center of the FEB RAS

Email: emb0909@rambler.ru
俄罗斯联邦, Khabarovsk

D. Tarkhov

Peter the Great Saint-Petersburg Politechnical University

Email: emb0909@rambler.ru
俄罗斯联邦, St. Petersburg

T. Shemyakina

Peter the Great Saint-Petersburg Politechnical University

Email: emb0909@rambler.ru
俄罗斯联邦, St. Petersburg

A. Vasilyev

Peter the Great Saint-Petersburg Politechnical University

Email: emb0909@rambler.ru
俄罗斯联邦, St. Petersburg

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