Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Maxim V. Zhukov"'
Publikováno v:
Вестник Северо-Кавказского федерального университета, Vol 0, Iss 1, Pp 132-137 (2022)
This paper discusses the reasons for the high level of losses and the possible solutions to this problem. A method of localization of non-technical losses of electricity on the basis of state estimation of currents based on voltage measurement is pro
Externí odkaz:
https://doaj.org/article/a9acc7f505474a3cb2eb9582adcc2cb0
Publikováno v:
International Journal of Mathematics and Mathematical Sciences, Vol 2018 (2018)
A method using radial basis function networks (RBFNs) to solve boundary value problems of mathematical physics is presented in this paper. The main advantages of mesh-free methods based on RBFN are explained here. To learn RBFNs, the Trust Region Met
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::47c360d24a29c41a7fb5821a2d4f6194
https://doi.org/10.1155/2018/9457578
https://doi.org/10.1155/2018/9457578
Publikováno v:
Автоматика и телемеханика. :95-105
We consider the solution of boundary value problems of mathematical physics with neural networks of a special form, namely radial basis function networks. This approach does not require one to construct a difference grid and allows to obtain an appro
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::293ff495e00372f4b1f03ab306bcdc49
https://doi.org/10.31857/s000523100001489-1
https://doi.org/10.31857/s000523100001489-1
Autor:
Maxim V. Zhukov, Vladimir Gorbachenko
Publikováno v:
Computational Mathematics and Mathematical Physics. 57:145-155
A neural network method for solving boundary value problems of mathematical physics is developed. In particular, based on the trust region method, a method for learning radial basis function networks is proposed that significantly reduces the time ne
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::db03bb9f353e0a01e0f2df8db66ea144
https://doi.org/10.1134/s0965542517010079
https://doi.org/10.1134/s0965542517010079
Autor:
Vladimir Gorbachenko, Maxim V. Zhukov, Alexander N. Vasilyev, Dmitriy Tarkhov, Tatiana V. Lazovskaya
Publikováno v:
Advances in Neural Networks – ISNN 2016 ISBN: 9783319406626
ISNN
ISNN
The general neural network approach to solving the inverse problems is considered. By applying the developed technique, we solve two different ill-posed problems. The first one is a coefficient inverse problem; the second one is an evolutionary inver
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::88ed0c37252c729e105fc00a45148278
https://doi.org/10.1007/978-3-319-40663-3_36
https://doi.org/10.1007/978-3-319-40663-3_36
