The effectiveness of the machine learning methods for real-world tasks depends on the proper structure of the modeling pipeline. The proposed approach is aimed to automate the …
Data-driven methods provide model creation tools for systems where the application of conventional analytical methods is restrained. The proposed method involves the data …
In this paper we demonstrate that reservoir computing can be used to learn the dynamics of the shallow-water equations. In particular, while most previous applications of reservoir …
M Maslyaev, A Hvatov - 2021 IEEE Congress on Evolutionary …, 2021 - ieeexplore.ieee.org
Usually, the data-driven methods of the systems of partial differential equations (PDEs) discovery are limited to the scenarios, when the result can be manifested as the single …
The paper presents the results of applying the generative design method to reconstruct a model driven by irregular data in the form of a partial differential equation. The problem of …
Data-driven surrogate models are widely used when the system dynamics equations and governing models are not known a priori. The form of the differential equation with the …
A Hvatov - arXiv preprint arXiv:2103.02294, 2021 - arxiv.org
The numerical solution methods for partial differential equation (PDE) solution allow obtaining a discrete field that converges towards the solution if the method is applied to the …