Zobrazeno 1 - 7
of 7
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
Publikováno v:
Advances in Neural Networks - ISNN 2016; 2016, pI-XX, 20p
This book constitutes the refereed proceedings of the 13th International Symposium on Neural Networks, ISNN 2016, held in St. Petersburg, Russia in July 2016. The 84 revised full papers presented in this volume were carefully reviewed and selected fr