SYNTHESIS OF SELF-ORGANIZING MAP AND FEEDFORWARD NEURAL NETWORK FOR BETTER FORECASTING

Authors

  • Oles Hodych
  • Yuriy Shcherbyna
  • Michael Zylan

DOI:

https://doi.org/10.47839/ijc.3.3.307

Keywords:

Artificial neural network, financial analysis, stock market, prediction

Abstract

In this article the authors propose an approach to forecasting the direction of the share price fluctuation, which is based on utilization of the Feedforward Neural Network in conjunction with Self-Organizing Map. It is proposed to use the Self-Organizing Map for filtration of the share price data set, whereas the Feedforward Neural Network is used to forecast the direction of the share price fluctuation based on the filtered data set. The comparison results are presented for filtered and non-filtered share price data sets.

References

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Published

2014-08-01

How to Cite

Hodych, O., Shcherbyna, Y., & Zylan, M. (2014). SYNTHESIS OF SELF-ORGANIZING MAP AND FEEDFORWARD NEURAL NETWORK FOR BETTER FORECASTING. International Journal of Computing, 3(3), 68-75. https://doi.org/10.47839/ijc.3.3.307

Issue

2004, Volume 3, Issue 3

Section

Articles

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