Please use this identifier to cite or link to this item:
https://elib.psu.by/handle/123456789/22789| Title: | Approximation of complex, multiparameter, essentially nonlinear, dynamic relationships based on genetic algorithms |
| Authors: | Glukhov, A. Glukhov, D. Trofimov, V. Trofimova, L. |
| Issue Date: | 2016 |
| Publisher: | IEEE |
| 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. pp. 252-254, doi: 10.1109/SCM.2016.7519744 |
| 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. |
| Keywords: | Genetic algorithms Complex Multiparameter Essentially nonlinear Dynamic dependencies Stock exchange index |
| URI: | https://elib.psu.by/handle/123456789/22789 |
| metadata.dc.identifier.doi: | 10.1109/SCM.2016.7519744 |
| Appears in Collections: | Публикации в Scopus и Web of Science |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 252-254.pdf | 328.21 kB | Adobe PDF | View/Open |
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