Zobrazeno 1 - 10
of 43
pro vyhledávání: '"Kimaev, A."'
Publikováno v:
Разработка и регистрация лекарственных средств, Vol 12, Iss 4, Pp 231-238 (2023)
Introduction. Cerebrovascular diseases (CVD) are one of the most pressing medical and social problems due to the high rate of mortality and disability. Stroke is the leading cause of CVD. About 15 million strokes are registered annually in the world
Externí odkaz:
https://doaj.org/article/7ced920a8fe14b76a409750c31396559
Autor:
E. B. Shustov, A. V. Bunjat, A. G. Platonova, O. M. Spasenkova, N. V. Kirillova, D. Yu. Ivkin, S. V. Okovityi, A. N. Kimaev
Publikováno v:
Разработка и регистрация лекарственных средств, Vol 10, Iss 4, Pp 206-214 (2021)
Introduction. Non-alcoholic fatty liver disease (NAFLD) is the most common liver disease in the world. Non-alcoholic steatohepatitis (NASH), a clinically progressive morphological form of NAFLD, ranks second in the list of reasons for liver transplan
Externí odkaz:
https://doaj.org/article/035cfcee0b7a412e9bdb6ac600dc60c9
Publikováno v:
In Chemical Engineering Research and Design September 2020 161:11-25
Publikováno v:
In Chemical Engineering Science 2 November 2019 207:1230-1245
Publikováno v:
In Chemical Engineering Research and Design December 2018 140:33-43
Publikováno v:
Chemical Engineering Research and Design. 161:11-25
The purpose of this study was to employ Artificial Neural Networks (ANNs) to develop data-driven models that would enable optimal control of a stochastic multiscale system subject to parametric uncertainty. The system used for the case study was a si
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::38165988c4258a9dcf25935ea053cbc7
https://doi.org/10.1016/j.cherd.2020.06.017
https://doi.org/10.1016/j.cherd.2020.06.017
Publikováno v:
Chemical Engineering Science. 207:1230-1245
The purpose of this study was to employ Artificial Neural Networks (ANNs) to develop data-driven models that would enable the shrinking horizon nonlinear model predictive control of a computationally intensive stochastic multiscale system. The system
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::dbbdd8cb75ebab8a0e4fe65863407fd7
https://doi.org/10.1016/j.ces.2019.07.044
https://doi.org/10.1016/j.ces.2019.07.044
Publikováno v:
Chemical Engineering Research and Design. 140:33-43
The purpose of this study is to adapt Multilevel Monte Carlo (MLMC) sampling technique for random noise estimation in stochastic multiscale systems and evaluate the performance of this method. The system under consideration was a simulation of thin f
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::dd53648c63cfb7e3f431a0b554543c6a
https://doi.org/10.1016/j.cherd.2018.10.006
https://doi.org/10.1016/j.cherd.2018.10.006
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Akademický článek
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