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pro vyhledávání: '"Turan, Evren"'
We use sensitivity analysis to design $\textit{optimality-based}$ discretization (cutting-plane) methods for the global optimization of nonconvex semi-infinite programs (SIPs). We begin by formulating the optimal discretization of SIPs as a max-min p
Externí odkaz:
http://arxiv.org/abs/2303.00219
Autor:
Turan, Evren Mert, Jäschke, Johannes
Publikováno v:
In Journal of Process Control November 2024 143
Autor:
Turan, Evren Mert, Jäschke, Johannes
Neural differential equations have recently emerged as a flexible data-driven/hybrid approach to model time-series data. This work experimentally demonstrates that if the data contains oscillations, then standard fitting of a neural differential equa
Externí odkaz:
http://arxiv.org/abs/2109.06786
Publikováno v:
In IFAC PapersOnLine 2024 58(14):767-774
Autor:
Turan, Evren Mert, Jäschke, Johannes
Publikováno v:
In Journal of Process Control January 2024 133
Publikováno v:
In IFAC PapersOnLine 2023 56(2):1394-1399
Autor:
Turan, Evren M. *, Jäschke, Johannes *
Publikováno v:
In IFAC PapersOnLine 2022 55(7):392-399
Publikováno v:
In Chemical Engineering Science 21 September 2021 241
Publikováno v:
In Advances in Space Research 1 April 2020 65(7):1852-1862
Publikováno v:
In Thin Solid Films 31 December 2019 692