Научный обзор докладов конференции "Третий Международный Семинар По Стохастическому Моделированию И Прикладным Исследованиям В Технологиях" – "The Third International Workshop On Stochastic Modeling And Applied Research Of Technology, Smarty 2022" (Петрозаводск, 21–25 Августа 2022)

Real-world networks display a strong heterogeneity that is reflected in a heavy-tailed distribution of node influence indices. The in-degree, the PageRank (PR) and the Max-Linear Model (MLM) may be used as node influence indices of random graphs. The indices are regularly varying heavy-tailed distributed random variables (r.v.s) . We predict the tail index (TI) and extremal index (EI) of the PRs and MLMs of newly appended nodes in evolved random networks.