Please use this identifier to cite or link to this item: http://elib.psu.by:8080/handle/123456789/22789
Title: Approximation of complex, multiparameter, essentially nonlinear, dynamic relationships based on genetic algorithms
Authors: Glukhov, A. O.
Glukhov, D. O.
Trofimov, V. V.
Trofimova, L. A.
Keywords: Genetic algorithms
Complex
Multiparameter
Essentially nonlinear
Dynamic dependencies
Stock exchange index
Issue Date: 2016
Citation: Glukhov, A. O. Approximation of complex, multiparameter, essentially nonlinear, dynamic relationships based on genetic algorithms / A. O. Glukhov, D. O. Glukhov, V. V. Trofimov, L. A. Trofimova // Proceedings of the XIX International Conference on Soft Computing and Measurements SCM`2016. St. Petersburg: IEEE, 2016. P. 252-254
Abstract: 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.
URI: http://elib.psu.by:8080/handle/123456789/22789
https://ieeexplore.ieee.org/document/7519744
Appears in Collections:Публикации авторов ПГУ в Scopus и Web of Science

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