Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Tamirat Temesgen Dufera"'
Publikováno v:
Mathematics, Vol 12, Iss 22, p 3483 (2024)
This paper proposes a deep neural network (DNN) model to estimate the Hurst exponent, a crucial parameter in modelling stock market price movements driven by fractional geometric Brownian motion. We randomly selected 446 indices from the S&P 500 and
Externí odkaz:
https://doaj.org/article/cee9695940d44854a7ba6ad222df40bb
Publikováno v:
Applied Computational Intelligence and Soft Computing, Vol 2024 (2024)
The nonlinear sine-Gordon equation is a prevalent feature in numerous scientific and engineering problems. In this paper, we propose a machine learning-based approach, physics-informed neural networks (PINNs), to investigate and explore the solution
Externí odkaz:
https://doaj.org/article/75bd79846a3a49efa22cb1edf26223e9
Publikováno v:
Mathematical Modelling and Analysis, Vol 27, Iss 3 (2022)
Potato virus Y (PVY) is an aphid-borne plant virus that causes substantial yield losses in potato production. Control measures of the viral infection are both limited and expensive. A proper use of mixed-cropping strategy can reduce the spread of PVY
Externí odkaz:
https://doaj.org/article/b1d3f1151791474d86b024b084added9
Publikováno v:
Journal of Mathematics, Vol 2022 (2022)
In this study, we examined the effect of three-sector interaction on business cycles in Keynesian models. Specifically, we considered the durable, fast, and investment-goods sectors. We modified and extended Murakami’s two-sector Keynesian model of
Externí odkaz:
https://doaj.org/article/feb5cfacea0b4d08ad2401f1bdd74c59
Publikováno v:
Applied Computational Intelligence and Soft Computing, Vol 2022 (2022)
The deep neural network (DNN) was applied for estimating a set of unknown parameters of a dynamical system whose measured data are given for a set of discrete time points. We developed a new vectorized algorithm that takes the number of unknowns (sta
Externí odkaz:
https://doaj.org/article/045c824e3bb043c298890eb3253b7408
Autor:
Tamirat Temesgen Dufera
Publikováno v:
Machine Learning with Applications, Vol 5, Iss , Pp 100058- (2021)
This paper is aimed at applying deep artificial neural networks for solving system of ordinary differential equations. We developed a vectorized algorithm and implemented using python code. We conducted different experiments for selecting better neur
Externí odkaz:
https://doaj.org/article/0c744882859047a7b9c35736d2d12b92
Publikováno v:
Applied Computational Intelligence and Soft Computing. 2022:1-10
The deep neural network (DNN) was applied for estimating a set of unknown parameters of a dynamical system whose measured data are given for a set of discrete time points. We developed a new vectorized algorithm that takes the number of unknowns (sta
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b818957ea9f25e961a2404ff8f2cff75
https://doi.org/10.1155/2022/2014510
https://doi.org/10.1155/2022/2014510
Publikováno v:
Integral Methods in Science and Engineering, Volume 1 ISBN: 9783319593838
In this paper, the Dirichlet boundary value problem for the second order “stationary heat transfer” elliptic partial differential equation with variable coefficient is considered in 2D. Using an appropriate parametrix (Levi function), this proble
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::43e2dd7a4836742c64fb71d6db92f626
https://doi.org/10.1007/978-3-319-59384-5_3
https://doi.org/10.1007/978-3-319-59384-5_3
