THE NEURAL NET APPROACH TO THE HARD TO FORMALIZE TASKS OF ANALYSIS AND PREDICTION

  • Abdiev Bolat Turar Ryskulov New Economic University
  • Madiyarova Kuralay Turar Ryskulov New Economic University
  • Ezhebekov Manat Turar Ryskulov New Economic University
Keywords: neural networks, self-organizing map, securities prices, multilayer network Kohonen

Abstract

The article discusses the use of neural networks and attempt to reveal the peculiarities of the different types of neural networks in the context of their application for the solution of difficult problems in formalized tasks, as well as how to improve the accuracy of forecasting financial performance, including securities prices. In particular, it discussed in more detail one of these models as a model of so-called self-organizing feature maps of Kohonen.

References

Кохонен Т. Ассоциативная память. М.: Мир, 1980, – 239 с.

Яковлев В.Л.,Яковлева Г.Л., Лисицкий Л.А. Модели детерминированного хаоса в задаче прогнозирование тенденции финансовых рынков и их нейросетевая реализация // Информационные технологии. 2000. No 2. С. 46 – 52.

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Published
2016-02-28
Citations
How to Cite
Abdiev Bolat, Madiyarova Kuralay, & Ezhebekov Manat. (2016). THE NEURAL NET APPROACH TO THE HARD TO FORMALIZE TASKS OF ANALYSIS AND PREDICTION. World Science, 2(2(6), 19-22. Retrieved from https://rsglobal.pl/index.php/ws/article/view/859
Issue
Vol 2 No 2(6) (2016): World Science
Section
Economy

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