UDC 004.92
METHODOLOGY AND ALGORITHMS FOR SOLVING THE INVERSE PROBLEM IN MODELING FRACTAL STRUCTURE GROWTH
A. A. Teplov, postgraduate student, Bauman Moscow State Technical University, Moscow, Russia;
orcid.org/0000-0002-1785-6089, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
The paper considers a methodology for solving the inverse problem in modeling the growth of fractal
structures with recovery of growth parameters from experimental data. A mathematical apparatus for recovering iterative parameters of growth process based on logistic regression and binary search algorithms is
proposed. An algorithm for searching temporal parameters with computational complexity O(log2N) ×
O(log2K) has been developed. Numerical experiments confirming the accuracy of parameter recovery have
been conducted. The results of modeling with analysis of error functional and iterative approximation are
presented. The methodology is applicable for designing fractal structures with specified characteristics in
software for computing systems.
Key words: inverse problem, fractal structures, logistic regression, binary search, growth parameters,
computational complexity, numerical modeling, parameter recovery