The method of estimation and forecasting in intelligent decision support systems was developed. The essence of the method is the analysis of the current state of the object and short-term forecasting of the object state. Objective and complete analysis is achieved by using improved fuzzy temporal models of the object state and an improved procedure for processing the original data under uncertainty. Also, the possibility of objective and complete analysis is achieved through an improved procedure for forecasting the object state and an improved procedure for learning evolving artificial neural networks. The concepts of fuzzy cognitive model are related by subsets of influence fuzzy degrees, arranged in chronological order, taking into account the time lags of the corresponding components of the multidimensional time series. The method is based on fuzzy temporal models and evolving artificial neural networks. The peculiarity of the method is the possibility of taking into account the type of a priori uncertainty about the object state (full awareness of the object state, partial awareness of the object state and complete uncertainty about the object state). The possibility to clarify information about the object state is achieved using an advanced training procedure. It consists in training 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 object state forecasting procedure allows conducting multidimensional analysis, consideration, and indirect influence of all components of a multidimensional time series with their different time shifts relative to each other under uncertainty. The method provides an increase in data processing efficiency at the level of 15–25% using additional advanced procedures.

The problem that is solved in the research is to increase the efficiency of decision making in management tasks while ensuring the given reliability, regardless of the hierarchical nature of the object. The object of the research is decision making support system. The subject of the research is the decision making process in management tasks using an improved wolf flock algorithm. The hypothesis of the research is to increase the efficiency of decision making with a given assessment reliability. In the course of the research, an improved optimization method based on an improved wolf flock algorithm was proposed. In the course of the conducted research, the general provisions of the theory of artificial intelligence were used to solve the problem of analyzing the objects state and subsequent parametric management in intelligent decision making support systems. The essence of the improvement lies in the use of the following procedures, which improve basic procedures of the wolf flock algorithm, namely search and chase: – taking into account the type of uncertainty of the initial data while constructing the wolf flock path metric; – searching for a solution in several directions using individuals from the wolf flock; – initial presentation of individuals from the wolf flock; – an improved procedure for adapting a flock of wolves; – taking into account the available computing resources while choosing the number of leaders in a flock of wolves. An example of the use of the proposed method is presented on the example of assessing the state of the operational situation of a group of troops (forces). The specified example showed an increase in the efficiency of data processing at the level of 23–30 % due to the use of additional improved procedures

The object of research is a special-purpose radio communication system. A special purpose radio communication system is affected by many different destructive influences. The main ones are deliberate interference and cybernetic impact of various purposes. The above causes the search for new scientific approaches to identify and identify the destructive impact on special-purpose radio communications in order to increase the operational efficiency of special-purpose radio communications systems. In this work, the problems of developing a mathematical model for managing the radio resource of special-purpose radio communication systems based on the evolutionary approach are solved. In the course of the research, the authors of the work used the main provisions of the theory of artificial intelligence, the theory of automation, the theory of complex technical systems, as well as general scientific methods of cognition, namely analysis and synthesis. The proposed methodological approach was developed taking into account the practical experience of the authors of this work during military conflicts of the last decade. The research results will be useful for: – development of new radio resource management algorithms; – substantiation of recommendations for improving the efficiency of radio resource operational management; – analysis of the radio-electronic situation during the conduct of hostilities (operations); – when creating promising technologies for increasing the efficiency of radio resource operational management; – assessment of the adequacy, reliability, sensitivity of the scientific and methodological apparatus for the operational management of the radio resource; – development of new and improvement of existing radio resource management models. Directions for further research will be aimed at developing a methodology for intelligent control of the radio resource of special-purpose radio communication systems.

The topicality of raising the level of rural territories’ energy independence is substantiated in the article. Using the Ukrainian and foreign experience in creating and implementing the projects “energy efficient village”, the stages of its introduction have been determined. Taking into account the results of these projects in Ukraine, the conditions as to providing their efficiency have been defined. The peculiarities of creating the energy independent and effective village have been considered; its conceptual model has been created. Some aspects of using biomass and its effectiveness as an alternative source of energy have been presented. The factors of ecological, social, and economic efficacy of developing and implementing the projects of “energy efficient village” on the rural territories of Ukraine have been determined. The actuality of developing and introducing the projects in the creation of energy independent rural territories is put into practice on the territory of Ukraine.

The features of modern military conflicts require significantly increasing requirements for the efficiency of determining a rational route for the transmission of information. It is necessary to develop algorithms (methods and techniques) that are able for a limited time and with a high degree of reliability to determine the rational route of information transmission in complex hierarchical information transmission systems. The following tasks were solved in the research: the task of information transfer in special purpose networks was set; the algorithm of realization of a method of efficiency increase of information transfer is defined; simulation of the process of information transfer in the communication networks of a group of troops (forces) was carried out. The essence of the proposed method is to use the ant algorithm and their further training. The method has the following sequence of actions: input of initial data; determining the degree of uncertainty and noise of the original data, determining the set of acceptable solutions, determining belonging to a certain class. The next step is to determine the route of information transfer, taking into account the impact of destabilizing factors, taking into account computing power and training ants. The novelty of the method is to take into account the type of uncertainty and noise in the data and take into account the available computing resources of the communication network. The novelty of the method also lies in the use of advanced training procedures using the apparatus of evolving artificial neural networks and selective use of system resources by connecting only the required number of agents (ants). The method allows to build a rational route of information transfer taking into account the influence of destabilizing factors. The use of the method allows to achieve an increase in the efficiency of information transfer at the level of 11-16% through the use of additional advanced procedures