Neural network approach to intricate problems solving for ordinary differential equations
- 作者: 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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隶属关系:
- Moscow Aviation Institute
- Computer Center of the FEB RAS
- Peter the Great Saint-Petersburg Politechnical University
- 期: 卷 26, 编号 2 (2017)
- 页面: 96-109
- 栏目: Article
- URL: https://journals.rcsi.science/1060-992X/article/view/194960
- DOI: https://doi.org/10.3103/S1060992X17020011
- ID: 194960
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详细
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
编辑信件的主要联系方式.
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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