In this paper a controller construction on the basis of the intelligent agent with fuzzy logic is considered. The algorithm of a fuzzy logic inference of the agent decision-making is described. Results of computer modelling of control process are received and analysed.

The control agent with fuzzy logic

/pdf/assessment-of-the-hydro-meteorological-conditions-impact-on-khyrrjrzbe.pdf

Assessment of the Hydro-Meteorological Conditions Impact on the Combat Troops Operations Preparation and Conduct in the Geo-Information Subsystem of the Automated Battlefield Management System.

/pdf/the-ontological-decision-support-system-composition-and-1oon9t6nsp.pdf

The Ontological Decision Support System Composition and Structure Determination for Commanders of Land Forces Formations and Units in Ukrainian Armed Force.

This article dwells upon phase shift determination method using total signal obtained as a result of summing up two harmonic signals after carrying out bisemiperiodic transformation, which can be attributed to measurement compensation method. Value of phase shift has been determined by comparing vector obtained after amplitude time analog-digital conversion of total signal with a set of reference function vectors. Maximum value of correlation coefficient has been used as criterion for specified vectors coincidence. Algorithm for finding the maximum correlation coefficient using golden section method has been developed. Main errors sources for proposed method of phase shift measurement have been determined. Application of proposed method in artificial intelligence system for diagnostic and determination of modern weapons and military equipment state will allow to reduce requirements for measuring equipment without reducing accuracy of measurements

Compensatory Method for Measuring Phase Shift Using Signals Bisemiperiodic Conversion in Diagnostic Intelligence Systems

/pdf/information-reference-system-creation-prerequisites-for-the-1ewnzumux5.pdf

Information-Reference System Creation Prerequisites for the Ground Forces Identification on the Battlefield According to NATO Standards.

Timely diagnostics of the technical state and technical support of complex multifaceted systems that provide comprehensive automation of control processes requires the development of new, high-precision and reliable troubleshooting methods. Using one of these methods may include a neural network apparatus.

/pdf/the-diagnostics-methods-for-modern-communication-tools-in-16d17y8wh8.pdf

The Diagnostics Methods for Modern Communication Tools in the Armed Forces of Ukraine Based on Neural Network Approach.

Attenuation of the signal propagating between the emitting and receiving antennas in a wireless network requires adaptation of the power of the emitted signal for the stable functioning of the network The random character of the signal attenuation, frequently leading to the so-called fading of the signal is a challenge demanding prediction of the signal intensity in each next time period We argue that the problem can be solved employing the fuzzy logic by loading the average values of signal attenuation during the 
$$n$$

 previous time intervals into the input of the neuro-fuzzy system A new method for adaptation of the power of radio transmitting devices based on the application of neuro-fuzzy systems is described The synthesized neuro-fuzzy system has the capability to select the set of input parameters depending on the features of the wireless network Training of such a system (for four input values) provides the prediction of the signal intensity with the accuracy of 97–98% The proposed method provides the adaption of the signal power in accordance with the requirements for the bandwidth capability of the radio path

Method of Power Adaptation for Signals Emitted in a Wireless Network in Terms of Neuro-Fuzzy System

This paper considers one of the stages of designing camouflage concealment means - the identification of characteristic colors of the terrain. Color is an integral part of the visual characteristic of camouflage means intended to conceal personnel, material resources, weapons and military equipment from enemy reconnaissance and destruction means. It is proposed to identify characteristic colors using cluster analysis, which refers to unsupervised machine learning methods. The number of clusters obtained determines the number of colors that will be displayed on the camouflage coating. As a result of the research, mathematical clustering algorithms were analyzed to determine the characteristic colors of the terrain. The need to conduct these studies is due to the lack of a universal way to determine the number of clusters, and is based on the research of other scientists who have determined that for each subject terrain only a certain clustering algorithm works most effectively, which must be determined experimentally. According to the results of the research, it was determined that the optimal algorithm for determining the characteristic colors of the terrain was the k-means++ clustering algorithm.

Clustering Methods Analysis for Terrain Colors Characteristics Determination

The subject matter of the article is transformation of information during combat sustainment at the tactical level. The goal of the study is to develop the method of collecting primary information is at the tactical level of the system of learning and implementing the experience of training and application of units of the Armed Forces of Ukraine. The tasks to be solved are: according to the main points of information theory to analyze the information of the learning and implementing the Armed Forces of Ukraine experience system and to assess the level of its qualitative characteristics; based on the analysis of the functional information transformation during combat sustainment in the observation plan to identify flows by kind of information; to formalize the mechanism of information transformation in the learning and implementing experience system according to the “black box” principle; to develop a sample questionnaire to answer the collection of primary information located at the tactical level of the learning and implementing the Armed Forces of Ukraine experience system. General scientific and special methods of scientific knowledge are used. The following results were obtained: Estimates of qualitative characteristics were calculated to determine ways of improvement the quality indicators of information circulating information in the learning and implementing the Armed Forces of Ukraine experience system. On the analysis of the functional transformation of the combat sustainment information in the observation plan the kinds of information were defined, namely the mechanism of transformation of information in the system was formalized according to the “black screen” principle. A toolkit in the form of detailed survey sheets was developed to collect the primary information at the tactical level of the learning and implementing the Armed Forces of Ukraine experience system and made it possible to increase estimates of qualitative characteristics about three-four times. Conclusions. Consideration of the system of learning and implementation of the experience of training and application of the Armed Forces from the point of view of the main provisions of the theory of information will allow to increase the effectiveness of the procedure, to determine the ways of improving the indicators of the quality of information. To improve the quality of incoming primary information in the learning and implementing the Armed Forces of Ukraine experience system, it is considered appropriate to develop tools for its collection in the form of detailed questionnaires. Information for the s learning and implementing experience system on the way of transformation is subjected to a procedure of certain unification, transformation and further separation according to functional characteristics for analysis. The process of preparing and conducting a battle in this case can be considered as a “black box”, which directly forms the experience.

Kind-time analysis of information for the learning and implementation of the experience in the preparation and use of sub-units of the armed forces of ukraine

Tetiana Lavrut

Papers

The Diagnostics Methods for Modern Communication Tools in the Armed Forces of Ukraine Based on Neural Network Approach.

Method of Power Adaptation for Signals Emitted in a Wireless Network in Terms of Neuro-Fuzzy System

Compensatory Method for Measuring Phase Shift Using Signals Bisemiperiodic Conversion in Diagnostic Intelligence Systems

Clustering Methods Analysis for Terrain Colors Characteristics Determination

Kind-time analysis of information for the learning and implementation of the experience in the preparation and use of sub-units of the armed forces of ukraine