Physics-informed recurrent neural networks and hyper-parameter optimization for dynamic process systems

Autor:	Tuse Asrav, Erdal Aydin
Rok vydání:	2023
Předmět:	General Chemical Engineering Computer Science Applications
Zdroj:	Computers & Chemical Engineering. 173:108195
ISSN:	0098-1354
DOI:	10.1016/j.compchemeng.2023.108195
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::82c4be66f7bc2aae36c8bd64d210bf6c https://doi.org/10.1016/j.compchemeng.2023.108195 Zobrazit plný text záznamu Full Text from ScienceDirect