Hybrid system of computational intelligence based on bagging and group method of data handling

Authors

  • Yevgeniy Bodyanskiy Kharkiv National University of Radio Electronics, Kharkiv, Ukraine https://orcid.org/0000-0001-5418-2143
  • Oleksii Kuzmenko Educational and Research Institute for Applied System Analysis of the National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", Kyiv, Ukraine https://orcid.org/0000-0003-1581-6224
  • Helen Zaichenko Educational and Research Institute for Applied System Analysis of the National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", Kyiv, Ukraine https://orcid.org/0000-0002-4630-5155
  • Yuriy Zaychenko Educational and Research Institute for Applied System Analysis of the National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", Kyiv, Ukraine https://orcid.org/0000-0001-9662-3269

DOI:

https://doi.org/10.20535/SRIT.2308-8893.2024.1.06

Keywords:

hybrid system, bagging, hybrid GMDH-neo-fuzzy network, ARIMA, short- and middle-term forecasting

Abstract

The paper considers the problem of short- and middle-term forecasting in the financial sphere. To solve this problem, a hybrid system of computational intelligence based on the group method of data handling (GMDH) and bagging, as well as an algorithm for its training, is proposed. The odd stacks of the hybrid system are formed by ensembles of parallel connected subsystems. ARIMA and the GMDH-neo-fuzzy hybrid network were chosen as such subsystems. The proposed system does not require a large training data set, automatically determines the number of stacks during training, and provides online operation. The experimental investigations were conducted using the proposed hybrid system, as well as separately using ARIMA and GMDH-neo-fuzzy. The accuracy of the predictions obtained is compared, based on which the feasibility of using the proposed hybrid system is substantiated.

Author Biographies

Yevgeniy Bodyanskiy, Kharkiv National University of Radio Electronics, Kharkiv

Doctor of Technical Sciences, a professor at the Artificial Intelligence Department of Kharkiv National University of Radio Electronics, Kharkiv, Ukraine.

Oleksii Kuzmenko, Educational and Research Institute for Applied System Analysis of the National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", Kyiv

Ph.D. student at Educational and Research Institute for Applied System Analysis of the National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", Kyiv, Ukraine.

Helen Zaichenko, Educational and Research Institute for Applied System Analysis of the National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", Kyiv

Doctor of Technical Sciences, a professor at the Department of Mathematical Methods of System Analysis of Educational and Research Institute for Applied System Analysis of the National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", Kyiv, Ukraine.

Yuriy Zaychenko, Educational and Research Institute for Applied System Analysis of the National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", Kyiv

Doctor of Technical Sciences, a professor at the Department of Mathematical Methods of System Analysis of Educational and Research Institute for Applied System Analysis of the National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", Kyiv, Ukraine.

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Published

2024-03-29

Issue

Section

Theoretical and applied problems of intelligent systems for decision making support