Development of a method for training artificial neural networks for intelligent decision support systems

Authors

DOI:

https://doi.org/10.15587/1729-4061.2022.251637

Keywords:

artificial neural networks, efficiency of information processing, decision support systems

Abstract

We developed a method of training artificial neural networks for intelligent decision support systems. A distinctive feature of the proposed method consists in training not only the synaptic weights of an artificial neural network, but also the type and parameters of the membership function. In case of impossibility to ensure a given quality of functioning of artificial neural networks by training the parameters of an artificial neural network, the architecture of artificial neural networks is trained. The choice of architecture, type and parameters of the membership function is based on the computing resources of the device and taking into account the type and amount of information coming to the input of the artificial neural network. Another distinctive feature of the developed method is that no preliminary calculation data are required to calculate the input data. The development of the proposed method is due to the need for training artificial neural networks for intelligent decision support systems, in order to process more information, while making unambiguous decisions. According to the results of the study, this training method provides on average 10–18 % higher efficiency of training artificial neural networks and does not accumulate training errors. This method will allow training artificial neural networks by training the parameters and architecture, determining effective measures to improve the efficiency of artificial neural networks. This method will allow reducing the use of computing resources of decision support systems, developing measures to improve the efficiency of training artificial neural networks, increasing the efficiency of information processing in artificial neural networks.

Author Biographies

Qasim Abbood Mahdi, Al Taff University College

PhD, Head of Department

Department of Computer Technology

Andrii Shyshatskyi, Central Scientific Research Institute of Armament and Military Equipment of the Armed Forces of Ukraine

PhD, Senior Researcher

Research Department of Electronic Warfare Development

Oleksandr Symonenko, Military Institute of Telecommunications and Information Technologies named after Heroes of Kruty

PhD, Senior Teacher

Department of Automated Control Systems

Nadiia Protas, Poltava State Agrarian University

PhD, Associate Professor

Department of Information Systems and Technologies

Oleksandr Trotsko, Military Institute of Telecommunications and Information Technologies named after Heroes of Kruty

PhD, Associate Professor

Department of Automated Control Systems

Volodymyr Kyvliuk, The National Defence University of Ukraine named after Ivan Cherniakhovsky

PhD, Associate Professor

Department of Logistic Support

Artem Shulhin, State Scientific-Research Institute of Aviation

PhD, Head of Research Department

Research Department

Petro Steshenko, State Scientific-Research Institute of Aviation

PhD, Leading Researcher

Research Department

Eduard Ostapchuk, Central Scientific Research Institute of Armament and Military Equipment of the Armed Forces of Ukraine

Deputy Head of the Research Department

Research Department for the Development of Protection and Survivability of Weapons and Military Equipment

Tetiana Holenkovska, Central Scientific Research Institute of Armament and Military Equipment of the Armed Forces of Ukraine

Researcher

Research Department of the Development of Communications and Technical Information Protection

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Published

2022-02-28

How to Cite

Mahdi, Q. A., Shyshatskyi, A., Symonenko, O., Protas, N., Trotsko, O., Kyvliuk, V., Shulhin, A., Steshenko, P., Ostapchuk, E., & Holenkovska, T. (2022). Development of a method for training artificial neural networks for intelligent decision support systems. Eastern-European Journal of Enterprise Technologies, 1(9(115), 35–44. https://doi.org/10.15587/1729-4061.2022.251637

Issue

Vol. 1 No. 9(115) (2022): Information and controlling system

Section

Information and controlling system

License

Copyright (c) 2022 Qasim Abbood Mahdi, Andrii Shyshatskyi, Oleksandr Symonenko, Nadiia Protas, Oleksandr Trotsko, Volodymyr Kyvliuk, Artem Shulhin, Petro Steshenko, Eduard Ostapchuk, Tetiana Holenkovska

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