Development of an improved method for finding a solution for neuro-fuzzy expert systems

Authors

DOI:

https://doi.org/10.15587/1729-4061.2020.211399

Keywords:

artificial intelligence, radio-electronic environment, intelligent systems, decision support systems

Abstract

Nowadays, artificial intelligence has entered into all spheres of human activity. However, there are some problems in the analysis of objects, for example, there is a priori uncertainty about the state of objects and the analysis takes place in a difficult situation against the background of intentional (natural) interference and uncertainty. The best solution in this situation is to integrate with the data analysis of information systems and artificial neural networks. This paper develops an improved method for finding solutions for neuro-fuzzy expert systems. The proposed method allows increasing the efficiency and reliability of making decisions about the state of the object. Increased efficiency is achieved through the use of evolving neuro-fuzzy artificial neural networks, as well as an improved procedure for their training. Training of evolving neuro-fuzzy artificial neural networks is due to learning their architecture, synaptic weights, type and parameters of the membership function, as well as the application of the procedure of reducing the dimensionality of the feature space. The analysis of objects also takes into account the degree of uncertainty about their condition. In the proposed method, when searching for a solution, the same conditions are calculated once, which speeds up the rule revision cycle and instead of the same conditions of the rules, references to them are used. This reduces the computational complexity of decision-making and does not accumulate errors in the training of artificial neural networks as a result of processing the information coming to the input of artificial neural networks. The use of the proposed method was tested on the example of assessing the state of the radio-electronic environment. This example showed an increase in the efficiency of assessment at the level of 20–25 % by the efficiency of information processing

Author Biographies

Olha Salnikova, Ivan Chernyakhovsky National Defense University of Ukraine Povitrofloski ave., 28, Kyiv, Ukraine, 03049

Doctor of Public Administration Sciences, Senior Researcher, Head of Educational and Research Center

Educational and Research Center of Strategic Communications in the sphere of National Security and Defense

Olga Cherviakova, East European Slavic University Gagarina str., 42-1, Uzhhorod, Ukraine, 88018

Doctor of Public Administration Sciences, Associate Professor, Vice-Rector for Scientific Work

Oleg Sova, Military Institute of Telecommunication and Information Technologies named after the Heroes of Kruty Moskovska str., 45/1, Kyiv, Ukraine, 01011

Doctor of Technical Sciences, Head of Department

Department of Automated Control Systems

Ruslan Zhyvotovskyi, Central Scientifically-Research Institute of Arming and Military Equipment of the Armed Forces of Ukraine Povitroflotskyi ave., 28, Kyiv, Ukraine, 03049

PhD, Senior Researcher, Head of Research Department

Research Department of the Development of Anti-Aircraft Missile Systems and Complexes

Serhii Petruk, Central Scientifically-Research Institute of Arming and Military Equipment of the Armed Forces of Ukraine Povitroflotskyi ave., 28, Kyiv, Ukraine, 03049

PhD, Deputy Chief of Research Department

Research Department of the Development of Anti-Aircraft Missile Systems and Complexes

Taras Hurskyi, Military Institute of Telecommunication and Information Technologies named after the Heroes of Kruty Moskovska str., 45/1, Kyiv, Ukraine, 01011

PhD, Associate Professor

Andrii Shyshatskyi, Central Scientifically-Research Institute of Arming and Military Equipment of the Armed Forces of Ukraine Povitroflotskyi ave., 28, Kyiv, Ukraine, 03168

PhD, Senior Researcher

Research Department of Electronic Warfare Development

Andrey Nos, Ivan Kozhedub Kharkiv National Air Force University Sumska st., 77/79, Kharkiv, Ukraine, 61023

PhD

Department of Physics and Radio Electronics

Yevhenii Neroznak, Military Institute of Telecommunication and Information Technologies named after the Heroes of Kruty Moskovska str., 45/1, Kyiv, Ukraine, 01011

Adjunct

Department of Automated Control Systems

Ihor Proshchyn, Ivan Chernyakhovsky National Defense University of Ukraine Povitrofloski ave., 28, Kyiv, Ukraine, 03049

Lecturer

Department of Strategic Communications

Educational and Research Center of Strategic Communications in the sphere of National Security and Defense

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Published

2020-10-31

How to Cite

Salnikova, O., Cherviakova, O., Sova, O., Zhyvotovskyi, R., Petruk, S., Hurskyi, T., Shyshatskyi, A., Nos, A., Neroznak, Y., & Proshchyn, I. (2020). Development of an improved method for finding a solution for neuro-fuzzy expert systems. Eastern-European Journal of Enterprise Technologies, 5(4 (107), 35–44. https://doi.org/10.15587/1729-4061.2020.211399

Issue

Vol. 5 No. 4 (107) (2020): Mathematics and Cybernetics - applied aspects

Section

Mathematics and Cybernetics - applied aspects

License

Copyright (c) 2020 Olha Salnikova, Olga Cherviakova, Oleg Sova, Ruslan Zhyvotovskyi, Serhii Petruk, Taras Hurskyi, Andrii Shyshatskyi, Andrey Nos, Yevhenii Neroznak, Ihor Proshchyn

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