Zobrazeno 1 - 10
of 112
pro vyhledávání: '"Kocijan, Jus"'
Publikováno v:
Chaos 1 July 2023; 33 (7): 073127
The performance of estimated models is often evaluated in terms of their predictive capability. In this study, we investigate another important aspect of estimated model evaluation: the disparity between the statistical and dynamical properties of es
Externí odkaz:
http://arxiv.org/abs/2307.09294
Non-parametric system identification with Gaussian Processes for underwater vehicles is explored in this research with the purpose of modelling autonomous underwater vehicle (AUV) dynamics with low amount of data. Multi-output Gaussian processes and
Externí odkaz:
http://arxiv.org/abs/2006.02194
Equation discovery methods enable modelers to combine domain-specific knowledge and system identification to construct models most suitable for a selected modeling task. The method described and evaluated in this paper can be used as a nonlinear syst
Externí odkaz:
http://arxiv.org/abs/1907.00821
Autor:
Hvala, Nadja, Mlakar, Primož, Grašič, Boštjan, Božnar, Marija Zlata, Perne, Matija, Kocijan, Juš
Publikováno v:
In Progress in Nuclear Energy April 2023 158
Publikováno v:
In IFAC PapersOnLine 2023 56(2):8314-8319
Autor:
Hvala, Nadja, Kocijan, Juš
Publikováno v:
In Computers and Chemical Engineering November 2021 154
Autor:
Krivec, Tadej, Kocijan, Juš, Perne, Matija, Grašic, Boštjan, Božnar, Marija Zlata, Mlakar, Primož
Publikováno v:
In Engineering Applications of Artificial Intelligence October 2021 105
Publikováno v:
In ISA Transactions March 2021 109:141-151
Publikováno v:
In Atmospheric Pollution Research February 2021 12(2):76-83