Zobrazeno 1 - 10
of 164
pro vyhledávání: '"equation discovery"'
Publikováno v:
IEEE Access, Vol 12, Pp 20574-20590 (2024)
The challenge in controlling a manipulator robot is to model the system to obtain an efficient control system design. One approach that can be used to model the dynamics of a manipulator robot is data-driven modeling. However, in its implementation,
Externí odkaz:
https://doaj.org/article/988b61169184495c824feaa8a63a5fe2
Publikováno v:
Mathematics, Vol 12, Iss 23, p 3745 (2024)
Equation discovery, also known as symbolic regression, is the field of machine learning that studies algorithms for discovering quantitative laws, expressed as closed-form equations or formulas, in collections of observed data. The latter is expected
Externí odkaz:
https://doaj.org/article/d4af84af4e0a4402875fb255b3133c9c
Publikováno v:
Naučno-tehničeskij Vestnik Informacionnyh Tehnologij, Mehaniki i Optiki, Vol 23, Iss 1, Pp 97-104 (2023)
In this article, an approach to modeling dynamical systems in case of unknown governing physical laws has been introduced. The systems of differential equations obtained by means of a data-driven algorithm are taken as the desired models. In this c
Externí odkaz:
https://doaj.org/article/33c48126e55e44c298ced2c3a4d8f33d
Autor:
Borja Bayón-Buján, Mario Merino
Publikováno v:
Machine Learning: Science and Technology, Vol 5, Iss 3, p 035057 (2024)
An algorithm to obtain data-driven models of oscillatory phenomena in plasma space propulsion systems is presented, based on sparse regression (SINDy) and Pareto front analysis. The algorithm can incorporate physical constraints, use data bootstrappi
Externí odkaz:
https://doaj.org/article/d5b766c8257f4073a8dbc45856a6df31
Autor:
Simone Manti, Alessandro Lucantonio
Publikováno v:
Machine Learning: Science and Technology, Vol 5, Iss 1, p 015005 (2024)
Computational modeling is a key resource to gather insight into physical systems in modern scientific research and engineering. While access to large amount of data has fueled the use of machine learning to recover physical models from experiments an
Externí odkaz:
https://doaj.org/article/88976e14543f49868169dde366e2e9cc
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Akademický článek
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Autor:
Takuya Suzuki
Publikováno v:
Japan Architectural Review, Vol 6, Iss 1, Pp n/a-n/a (2023)
Abstract Many studies have been conducted to elucidate unknown input/output systems based on measured data obtained from experiments and observations. Specifically, neural networks, which have been significantly developed in recent years, can be used
Externí odkaz:
https://doaj.org/article/7997c8aab33a48e88b7b3d5813a37834
Akademický článek
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Autor:
Stefan Hiemer, Stefano Zapperi
Publikováno v:
Materials Theory, Vol 5, Iss 1, Pp 1-9 (2021)
Abstract A time-honored approach in theoretical materials science revolves around the search for basic mechanisms that should incorporate key feature of the phenomenon under investigation. Recent years have witnessed an explosion across areas of scie
Externí odkaz:
https://doaj.org/article/aeeea992c24e4044a647fb78c8ce9233