e-Article
MACHINE LEARNING MODELS TO DETERMINE UNOBSERVABLE CENTRALITY-RELATED PARAMETER VALUES FOR A WIDE RANGE OF NUCLEAR СOLLISIONS AT THE ENERGY OF 200 GeV
Document Type
Article
Author
Source
In: St. Petersburg State Polytechnical University Journal: Physics and Mathematics . (St. Petersburg State Polytechnical University Journal: Physics and Mathematics, 2023, 16(2):111-120)
Subject
Language
English
ISSN
26188686
23049782
23049782