Development of a method of complex analysis and multidimensional forecasting of the state of intelligence objects

Authors

DOI:

https://doi.org/10.15587/1729-4061.2023.276168

Keywords:

multidimensional forecasting, artificial intelligence, bio-inspired algorithms, heterogeneous intelligence objects

Abstract

A method of complex analysis and multidimensional forecasting of the state of intelligence objects is proposed to increase the accuracy of their state assessment. The object of research is decision support systems. The subject of research is the process of decision-making in management problems using artificial intelligence methods. The hypothesis of research is to increase the efficiency of decision-making with a given assessment reliability. The proposed method is based on a combination of fuzzy cognitive and temporal models, an advanced cat swarm optimization algorithm and evolving artificial neural networks. The method has the following sequence of actions:

‒ input of initial data;

‒ processing of initial data taking into account uncertainty about the state of heterogeneous intelligence objects;

‒ construction of a fuzzy temporal ontological model of heterogeneous intelligence objects;

‒ conclusion on the state of heterogeneous intelligence objects;

‒ correction of the fuzzy temporal ontological model;

‒ building a fuzzy relational temporal cognitive model of heterogeneous intelligence objects and forecasting the state of the intelligence object;

‒ training knowledge bases on heterogeneous intelligence objects.

The training procedure consists in learning the synaptic weights of the artificial neural network, the type and parameters of the membership function, as well as the architecture of individual elements and the architecture of the artificial neural network as a whole. The method makes it possible to increase the efficiency of data processing at the level of 18–25 % by using additional improved procedures. The proposed method should be used to solve the problems of evaluating complex and dynamic heterogeneous intelligence objects, characterized by a high degree of complexity.

Author Biographies

Olena Nechyporuk, National Aviation University

Doctor of Technical Sciences, Associate Professor

Department of Computerized Control Systems

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

Doctor of Technical Sciences, Senior Research, Head of Department

Department of Automated Control Systems

Andrii Shyshatskyi, Research Center for Trophy and Perspective Weapons and Military Equipment

PhD, Senior Researcher, Head of Department

Department of Robotic Systems Research

Serhii Kravchenko, National Aviation University

PhD, Associate Professor

Department of Software Engineering

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

PhD, Senior Research

Scientific-Research Laboratory of Automation of Scientific Researches

Oleh Shknai, Scientific-Research Institute of Military Intelligence

PhD, Leading Researcher

Scientific-Research Department

Serhii Klimovych, Military Institute of Telecommunications and Information Technologies named after Heroes of Kruty

PhD, Head of Department

Department of Information Protection in Telecommunication Systems and Networks

Olha Kravchenko, National Aviation University

Assistant

Department of Software Engineering

Oleksandr Kovbasiuk, Central Scientifically-Research Institute of Armaments and Military Equipment of the Armed Forces of Ukraine

PhD, Head of Scientific-Research Department

Scientific-Research Department

Anton Bychkov, Central Scientifically-Research Institute of Armaments and Military Equipment of the Armed Forces of Ukraine

PhD, Head

Scientific-Research Laboratory of Automation of Scientific Researches

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Development of a method of complex analysis and multidimensional forecasting of the state of intelligence objects

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Published

2023-04-29

How to Cite

Nechyporuk, O., Sova, O., Shyshatskyi, A., Kravchenko, S., Nalapko, O., Shknai, O., Klimovych, S., Kravchenko, O., Kovbasiuk, O., & Bychkov, A. (2023). Development of a method of complex analysis and multidimensional forecasting of the state of intelligence objects . Eastern-European Journal of Enterprise Technologies, 2(4 (122), 31–41. https://doi.org/10.15587/1729-4061.2023.276168

Issue

Vol. 2 No. 4 (122) (2023): Mathematics and Cybernetics - applied aspects

Section

Mathematics and Cybernetics - applied aspects

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Copyright (c) 2023 Olena Nechyporuk, Oleg Sova, Andrii Shyshatskyi, Serhii Kravchenko, Oleksii Nalapko, Oleh Shknai, Serhii Klimovych, Olha Kravchenko, Oleksandr Kovbasiuk, Anton Bychkov

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