Approximation of complex, multiparameter, essentially nonlinear, dynamic relationships based on genetic algorithms
A. O. Glukhov, D. O. Glukhov, V. V. Trofimov, L. A. Trofimova · 2016
The work is focused on usage of genetic algorithms to get more precise approximation of complex and essentially nonlinear dynamic relationships. The algorithms precision was measured based on the model of stock market index prediction.