Recent publications

Existing remote monitoring technologies provide farmers with useful information about the current health status of crops. The ability of remote sensors to detect subtle differences in vegetation makes them indispensable tools for precision farming, providing a quantitative assessment of crops in a particular area of the field. Multispectral data from such sounding allows farmers to obtain the vegetation maps, reflecting the current state of crops. Such vegetation maps allow to analyze the state of plants in dynamics, as well as to predict yields. In precision agriculture, for the numerical interpretation of multispectral data, vegetation indices are used. These indices are obtained empirically, i.e., by conducting experiments with different wavelength ranges in the electromagnetic spectrum. The given article considers the annual dynamics of the development of the plant culture in a particular field by analyzing the corresponding time series of a particular vegetation index. The possibility of predicting the yield of a particular crop based on fuzzy modeling of such time series is considered.

The article suggests a fuzzy approach to safe navigation when changing lanes in a road scenario. The approach is to create a module for making informed decisions during lane changes by several agents in order to avoid collisions. The price libraries used in this model help to make decisions when changing lanes. The article describes two modules two fuzzy modules, a fuzzy target control module, and a fuzzy collision avoidance control module are designed to perform these two tasks.
As a result, with the help of dynamic fuzzy clustering methods, adaptive driving of an unmanned vehicle (DUV) management is supported, which allows for minimizing the risks of road accidents (accidents involving DUV) and maximizing traffic (total output flow) in conditions of intense traffic flow.
In the article, the simulation of a robot car moving along the lane and changing the lane of the Road is implemented in the Matlab environment.
KeywordsAutonomous vehiclesMotion planning; fuzzy logicEvolutionary fuzzy inference systemsTraffic simulationMulti-robot motion planningUnmanned transport systemsIntelligent transport systemSimulation modelingFuzzy logic

Some territories where economic activity is carried out are characterized by the presence of mountain and forest tracts. To provide information support for the development of infrastructure and agriculture in these areas, in some cases overland monitoring using unmanned technologies is required. In this regard, an algorithm for the formation of a 3D trajectory of a quadcopter during overland piloting in a mountainous and wooded landscape is proposed, which implies autonomous maneuvering to overcome possible obstacles. As a basic model, it is proposed to use a fuzzy inference system with input characteristics in the form of linguistic variables that reflect fuzzy sectors of space, within which the presence of obstacles and the distance to them are interpreted verbally, that is, in the form of terms of corresponding input linguistic variables. Overcoming obstacles is supposed to be performed based on fuzzy conclusions of the proposed system, formulated as terms of output linguistic variables, which reflect changes in the angle of rotation in the horizontal plane, flight altitude and traverse speed of the quadcopter. The given paper analyzes the results of the model behavior for different scenarios of the terms of the input linguistic variables.

This article sets out the methodology for evaluation of expert opinions on agricultural structure of sown areas that is one of main factors constituting food security. For this purpose, the theory and instruments of fuzzy Z-numbers have been employed. The Z-number theory opened a new window of opportunities for many applications, especially in the areas of computation with probabilities and events stated in natural language. From this perspective, Z-numbers theory is an effective tool to make synthesis and analysis of expert opinions. In this paper, we try to determine the best case among expert opinions. Firstly, on the basis of subjective expert evaluations, corresponding Z-numbers are constructed. Then, in order to establish the medium version of expert opinions, addition and averaging operations on Z-numbers have been carried out. As a result, the intermediate of the expert opinions is assessed, then the best case is selected which may be accepted as the desired agricultural structure of sown areas of cereal and leguminous plants in Azerbaijan for the upcoming years.

The main goal of scientific research on the development of intelligent object management systems is to ensure that the system can process not only data of a numerical type, but also various types of data, such as image, writing, speech, and operator-controlled systems are replaced by objects that have intelligent management. The increased performance of modern information systems makes it possible to use more complex algorithms for processing and analyzing digital images. The article proposes a fuzzy approach to the processing of images. Descriptive information and the concept of description are mainly covered by uncertainty. Fuzzy logic is a good mathematical basis for working with uncertain information. Using this methodology, the uncertainty in image concepts was manipulated. The increase in the computing power of visual sensors, as well as the ability to process large amounts of information from the scene of an accident, allows for mapping, localization, autonomous navigation, route tracking, etc. this was the main tool for creating visibility in applications such as. The mobile robot is mentioned as the basis for making decisions based on fuzzy visual information, and intelligent algorithms used in robotics have been considered. During the initial preparation of the image for recognition, the main problems, as well as their solutions are considered.

The main criteria and source of economic development is economic growth. Economic growth is a sustainable increasing tendency of the main indicators of national theory production – gross national income (GNI) and gross domestic product (GDP). Furthermore, absolute value and per capita growth are also considered. In economics and statistics, various indicators are used to measure the amount of national production. The most important of these is gross domestic product. GDP is expressed by monetary unit of the final products and services produced in the economy. Here, it should be taken into account that GDP is comprised of final products and services produced within the particular country. In this work, fuzzy inference logic system was applied to the dynamic model that demonstrates the dependence of GDP on currency and oil price in case of Azerbaijan economy. To solve this dynamic problem some coefficients, need to be defined. Fuzzy inference logic method was suggested to define these coefficients. Fuzzy inference logic method was realized by MATLAB Software Package.

The digitalization of the state economy implies the formation of a stable and secure information and telecommunications infrastructure for high-speed transmission; the ability to store and process large amounts of data, accessible to all organizations and households; the use of advanced software by government agencies, local governments, and organizations. Obviously, the main benefits from the digitalization of the economy lie in the plane of solving problems related to productivity growth, cost minimization, automation, and production efficiency. It is possible to analyze levels of data that are beyond human understanding, which in turn allows companies to personalize experiences, customize products (services) and identify growth opportunities with speed and accuracy that were not possible before. However, the implementation of the Digital Economy project is only the first step towards creating the image of the economy of the near future. According to the unanimous opinion of experts, the main “actor” that allows consumers and businesses to get the maximum benefit out of the Digital Economy will be Artificial Intelligence, which will significantly change the world and will be used everywhere in the economy. Companies that do not consider the phenomenon of Artificial Intelligence and do not respond to its penetration into day-to-day life are not capable of innovating and reengineering their business models. At best, these companies will lose their competitive advantage, and at worst, they will simply disappear.

The paper is devoted to the boundary controllability of the abstract wave equations when the control is exerted on a part of the boundary by means of one control. We give a Kalman-type condition and give a description of the attainable set. The equation includes a linear operator A defined in a Hilbert space H, in which by choosing H and A, we can obtain boundary controllability properties of numerous classes of nonlocal mixed value problems for wave equations which occur in a wide variety of physical systems. In this respect, we derived boundary controllability properties of the mixed problem for infinite many systems of wave equations, nonlocal mixed problem for degenerate wave equations and for high-order wave equations.

The problem of optimal control of systems of linear two- dimensional difference equations of fractional order is considered. A number of optimality conditions are established.

Models of double-source queuing-inventory systems are studied in the presence of a finite buffer for waiting in the queue of consumer customers, where instant destruction of inventory is possible. It is assumed that the lead times of orders, as well as the cost of delivery from various sources, differ from each other. Replenishment of stocks from various sources is carried out according to the following scheme: if the inventory level drops to the reorder point s, then a regular order for the supply of inventory to a slow source is generated; if the inventory level falls below a certain threshold value r, where r < s, then the system instantly cancels the regular order and generates an emergency order to the fast source. Models of systems that use (s, S) or (s, Q) replenishment policies are studied. Exact and approximate methods for finding the performance measures of the models under study are proposed. The problems of minimizing the total cost are solved by choosing the appropriate values of the parameters s and r when using different replenishment policies. Numerical examples demonstrated the high accuracy of an approximate method as well as compared performance measures of the system under various replenishment policies.

In this paper, we consider an optimal control problem in which a dynamical system is controlled by a nonlinear Caputo fractional state equation. The problem is investigated in the case when the Pontryagin maximum principle degenerates, that is, it is satisfied trivially. Then the second order optimality conditions are derived for the considered problem.

The article is devoted to the development of algorithms for calculating the cross-correlation function and the correlation coefficient between the useful signal and the noise of a noisy signal. The authors analyze the factors influencing the adequacy of the results of solving the problems of monitoring, control, management, etc. It is noted that when processing noisy signals, algorithms and technologies for separate processing of the useful component and the noise should be used. It is shown that in the event of malfunctions, such an important condition as the absence of correlation between the useful signal and the noise is violated in monitoring and control systems. Therefore, the problem arises of calculating the crosscorrelation function and the correlation coefficient between the useful signal and the total noise as well. Algorithms are proposed for calculating the estimates of the correlation coefficient and the correlation function between the useful signal and the noise of noisy signals. It is pointed out that the moment of occurrence of the correlation between the useful signal and the noise can be monitored in real time in information systems. It is shown that the estimate of the variance of the total noise before the appearance of the correlation is a stable value. When a correlation appears, the value of the variance of the total noise changes. The difference in the variance estimates is taken as an analogue of the estimate of the cross-correlation function between the useful signal and the noise at zero time shift.A technology for conducting computational experiments is proposed. Discrete values of the useful signal, noise and noisy signal are generated. The correlation coefficient and the cross-correlation function between the useful signal and the noise are calculated by the developed and traditional algorithms. A comparative analysis is carried out. It is shown that the proposed technologies for calculating the estimates of the cross-correlation function and the correlation coefficient between the useful signal and the noise, as well as the variance of the total noise, make it possible to extract additional important information from noisy signals. This opens up the opportunity to increase the efficiency of the analysis of noisy signals.

In control theory, there is growing interest in the evolution of sets, especially integral funnels and reachable sets at a certain time. In this paper, we establish sufficient conditions for the convexity of reachable sets for an object whose behavior is described by the second-order differential inclusions. This fact is proved using the concavity of the Hamilton function in the first argument. Further, in connection with the usefulness of the Hamilton function, some of its properties, such as continuity and Lipschitz property, are investigated. At the end of the article, the results obtained are demonstrated with some examples.

The purpose of this paper is to investigate the duality for optimal control problems with higher-order differential inclusions. Using locally adjoint mappings and the discretization method, we derive the conditions of optimality for a boundary-value problem with higher-order differential inclusions. This method connects a duality relation problem to a continuous concerning problem. Then, thanks to the dual operations of addition and infimal convolution of convex functions, we obtain duality results. In general, the construction of the duality problem with the assistance of discrete and discrete approximation problems necessitates a significant amount of effort to comprehend the computational aspects. Finally, we show that the optimal solutions to the primal convex and dual concave problems are the same.

This paper determines whether road-fuel (gasoline plus diesel) income and price elasticities have changed over time in middle-income countries. To do so, the paper considers a balanced panel of 26 countries that spans 1990–2019. Also, the paper employs two methods that fully allow for cross-sectional heterogeneity, but vary to the extent that they allow for temporal heterogeneity: rolling window, mean group regressions and mean observation OLS, which estimates coefficients for each cross-section and each time period. While the elasticities demonstrate some temporal heterogeneity, such variances are less pronounced than the corresponding country-level heterogeneity. At any point in time, for middle-income countries, the average road-fuel income elasticity is between 1 and 0.8, and the average road-fuel price elasticity is very near −0.2. Lastly, we find no strong evidence that road-fuel demand has become saturated or that efficiency improvements have made consumers less price sensitive in middle-income countries.

В статье исследуется процесс восстановления с вознаграждением с зависимыми компонентами. Получено асимптотическое разложение для математического ожидания процесса в случае, когда интервалы времени между приходами имеют распределения с тяжелыми хвостами.

The article considers a high-order optimal control problem and its dual problems described by high-order differential inclusions. In this regard, the established Euler–Lagrange type inclusion, containing the Euler–Poisson equation of the calculus of variations, is a sufficient optimality condition for a differential inclusion of a higher order. It is shown that the adjoint inclusion for the first-order differential inclusions, defined in terms of a locally adjoint mapping, coincides with the classical Euler–Lagrange inclusion. Then the duality theorems are proved.

We consider a multi-server production inventory system with an unlimited waiting line. Arrivals occur according to a non-homogeneous Poisson process and exponentially distributed service time. At the service completion epoch, one unit of an item in the on-hand inventory decreases with probability δ, and the customer leaves the system without taking the item with probability (1−δ). The production inventory system adopts an (s,S) policy where the processing of inventory requires a positive random amount of time. The production time for a unit item is phase-type distributed. Furthermore, assume that an emergency replenishment of one item with zero lead time takes place when the on-hand inventory level decreases to zero. The emergency replenishment is incorporated in the system to ensure customer satisfaction. We derive the stationary distribution of the system and some main performance measures, such as the distribution of the production on/off time in a cycle and the mean emergency replenishment cycle time. Numerical experiments are conducted to illustrate the system performance. A cost function is constructed, and we examine the optimal number of servers to be employed. Furthermore, we numerically calculate the optimal values of the production starting level and maximum inventory level.

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