Development of assessment and forecasting techniques using fuzzy cognitive maps

Authors

DOI:

https://doi.org/10.15587/2706-5448.2023.281892

Keywords:

artificial intelligence, analysis objects, complex technical systems, vague cognitive maps, uncertainty

Abstract

Nowadays, no state in the world is able to work on the creation and implementation of artificial intelligence (AI) in isolation from others. AI technologies are used to solve general and highly specialized tasks in various spheres of society. In the process of assessing (identifying) the state of complex objects and objects of management analysis, there is a high degree of a priori uncertainty regarding their state and a small amount of initial data describing them. At the same time, despite the huge amount of information, the degree of non-linearity, illogicality and noisy data is increasing. That is why the issue of improving the efficiency of assessing the condition of components and objects is an important issue. Thus, the objects of analysis were chosen as the research object. The subject of research is the identification and forecasting of the analysis object.

In the research, the evaluation and forecasting method was developed using fuzzy cognitive maps. The features of the proposed method are:

‒ taking into account the degree of uncertainty about the object state while calculating the correction factor;

‒ adding a correction factor for data noise as a result of distortion of information about the object state;

‒ reduction of computing costs while assessing the object state;

‒ creation of a multi-level and interconnected description of hierarchical objects;

‒ correction of the description of the object as a result of a change in its current state using a genetic algorithm;

‒ the possibility of performing calculations with source data that are different in nature and units of measurement.

It is advisable to implement the proposed method in specialized software, which is used to analyze the state of complex technical systems and while making decisions.

Author Biographies

Andrii Shyshatskyi, Taras Shevchenko Kyiv National University

PhD, Senior Researcher

Educational and Scientific Institute of Public Administration and Civil Service

Oleg Sova, Kruty Heroes Military Institute of Telecommunications and Information Technologies

Doctor of Technical Science, Professor, Head of Department

Department of Automated Control Systems

Tetiana Stasiuk, Military Institute of Telecommunications and Information Technologies named after Heroes of Kruty

Lecturer

Cyclic Commission of General Education Disciplines

Sergeant Military College

Vitalii Andronov, Research Institute of Military Intelligence

PhD, Head of Department

Oleksii Nalapko, Central Scientifically-Research Institute of Armaments and Military Equipments of the Armed Forces of Ukraine

PhD, Senior Researcher

Scientific-Research Laboratory of Automation of Scientific Researches

Nadiia Protas, Poltava State Agrarian University

PhD, Associate Professor

Department of Information Systems and Technologies

Gennady Pris, Kruty Heroes Military Institute of Telecommunications and Information Technologies

Deputy Head

Scientific Center of Communication and Informatization

Roman Lazuta, Kruty Heroes Military Institute of Telecommunications and Information Technologies

Head of Department

Scientific Research Department

Scientific Center for Communication and Informatization

Illia Kovalenko, Kruty Heroes Military Institute of Telecommunications and Information Technologies

Senior Researcher

Scientific Research Department

Bohdan Kovalchuk, Kruty Heroes Military Institute of Telecommunications and Information Technologies

Junior Researcher

Scientific Research Department

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Development of method for identifying the state of various dynamic objects

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Published

2023-06-15

How to Cite

Shyshatskyi, A., Sova, O., Stasiuk, T., Andronov, V., Nalapko, O., Protas, N., Pris, G., Lazuta, R., Kovalenko, I., & Kovalchuk, B. (2023). Development of assessment and forecasting techniques using fuzzy cognitive maps. Technology Audit and Production Reserves, 3(2(71), 15–19. https://doi.org/10.15587/2706-5448.2023.281892

Issue

Vol. 3 No. 2(71) (2023): Information and control systems

Section

Systems and Control Processes

License

Copyright (c) 2023 Andrii Shyshatskyi, Oleg Sova, Tetiana Stasiuk, Vitalii Andronov, Oleksii Nalapko, Nadiia Protas, Gennady Pris, Roman Lazuta, Illia Kovalenko, Bohdan Kovalchuk

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