Abstract:
Currently, entropy is quite often used to describe complex systems in various fields. The questions of using differential entropy for network structures presented in the form of connected graphs with correlations are considered. It is well known that the entropy of a continuous random vector can be split into two components, the entropy of randomness and the entropy of self-organization. Along with the assessment of the entropy itself, other useful characteristics have been proposed for network structures, the entropy measure of the relationship between several subsystems and the entropy of the system at a separate vertex; these expand the possibilities of entropy modeling for the study of network structures and allow estimating the interconnection of different sections with each other and determining how entropy within such systems changes. Examples on model data are considered.
This publication is cited in the following 3 articles:
A. N. Tyrsin, S. E. Kascheev, “Modelirovanie vzaimovliyaniya skvazhin dlya analiza effektivnosti sistem zavodneniya na malykh vyborkakh dannykh”, UBS, 111 (2024), 247–265
Alexander N. Tyrsin, Stanislav E. Kashcheev, Michael Beer, Olga M. Gerget, Studies in Systems, Decision and Control, 560, Cyber-Physical Systems, 2024, 219
Yi Chen, Lu Liu, Xiaomeng Zhang, Wei Qiao, Ranzhen Ren, Boyu Zhu, Lichuan Zhang, Guang Pan, Yang Yu, “Critical Node Identification of Multi-UUV Formation Based on Network Structure Entropy”, JMSE, 11:8 (2023), 1538