The Hierarchical Model of Interaction Between Intelligent Agents in The Manet Control Systems

The hierarchical model of interaction between intelligent agents in the MANET control systems is proposed in the paper. Proposed model is based on the conceptual representation of the intelligent MANET control systems as a hierarchical structure with vertical connections that define management tasks subordination in the MANET

Development of A Complex Method for Finding A Solution for Neuro-fuzzy Expert Systems

Artificial intelligence has become the backbone of modern decision support systems. This is why a complex method for finding solutions for neuro-fuzzy expert systems has been developed. The proposed complex method is based on a mathematical model for the analysis of the operational situation. The model makes it possible to determine the parameters of the analysis of the operational situation, their influence on the quality of assessment of the operational situation and to determine their number with units of measurement. An increase in the efficiency of information processing (error reduction) of the assessment is achieved by the use of evolving neuro-fuzzy artificial neural networks. Training of evolving neuro-fuzzy artificial neural networks is carried out by training not only synaptic weights of the artificial neural network, the type, parameters of the membership function, but also by applying the procedure for reducing the dimension of the feature space. The efficiency of information processing is also achieved by training the architecture of artificial neural networks; accounting for the type of uncertainty in the information to be assessed; work with both clear and fuzzy data. We achieved a reduction in computational complexity while making decisions; the absence of errors in training artificial neural networks as a result of processing information entering the input of artificial neural networks. The analysis of the operational situation as a whole occurs due to the improved clustering procedure, which allows working with both static and dynamic data. The proposed complex method was tested on the example of assessing the state of the operational situation. The mentioned example showed an increase in assessment efficiency at the level of 20–25 % in terms of information processing efficienc

Development of A Method of Multi-criteria Evaluation Under Uncertainty

The object of research is decision-making support systems. Local wars and armed conflicts of recent decades are characterized by high dynamics of operations (combat operations) and a significant amount of diverse information circulating in information systems. These features determine the search for new approaches to increase the efficiency of decision-making support systems, given their reliability. This article solves the problem of developing a method of multicriteria evaluation in conditions of uncertainty. In the course of the research, the authors used the main provisions of the theory of artificial intelligence, automation theory, theory of complex technical systems and general scientific methods of cognition, namely analysis and synthesis. The proposed methodology was developed taking into account the practical experience of the authors of this work during the military conflicts of the last decade. The method of multicriteria evaluation is universal and can be used to assess the state of the objects of analysis of any architecture. The results of the research will be useful in: – development of new control algorithms in decision-making support systems; – substantiation of recommendations for improving the efficiency of operational management; – analysis of analysis (monitoring) objects in the course of hostilities (operations); – creation of perspective technologies to increase the efficiency of operational management; – assessment of the adequacy, reliability, sensitivity of the scientific and methodological apparatus of operational management in decision-making support systems; – development of new and improvement of existing management models. Areas of further research will be aimed at developing a methodology for intelligent management in special-purpose decision-making support systems

Analysis of Mathematical Models of Mobility of Communication Systems of Special Purpose Radio Communication Systems

The object of research is the military radio communication system. One of the problems in improving the effectiveness of military radio communication systems is the correct description of the movement process in them. Efficient routing protocols are only possible if reliable information on network topology for network nodes is available. Thus, with this information, packets can be forwarded correctly between the sender and the recipient. Given that the mobility of individual nodes is insignificant in special wireless networks, nodes in the network show the mobility properties of a group of nodes. This observation is directly related to the very existence of military wireless networks with the ability to organize themselves, that is, to support group cooperation and group activities. In this work the problem of analysis (decomposition) of the mobility models of military radio communication networks with the possibility of self-organization is solved. The classification of mobility patterns, the description of individual mobility models and the analysis of various aspects currently available, as well as those properties lacking in the attempt to simulate the movement of individual nodes, have been carried out. During the research, the analysis of random, semi-deterministic and deterministic models was carried out. The advantages and disadvantages of the above models have been identified. In the course of the research, the authors of the work used the main principles of the theory of mass service, the theory of automation, the theory of complex technical systems, as well as general scientific methods of knowledge, namely analysis and synthesis. The research results will be useful in: ‒ synthesis of mathematical models of node mobility; ‒ evaluation of the effectiveness of the science-based tool for assessing the mobility of nodes; ‒ validation of recommendations to improve the efficiency of mobile radio networks; ‒ analysis of the radio-electronic situation during the conduct of military operations (operations); ‒ creating advanced technologies to improve the efficiency of mobile radio networks

Development of an Improved Method for Finding A Solution for Neuro-fuzzy Expert Systems

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 processin