Mathematical Modeling Tools Research Articles

Estimating the economic impact of COVID-19 disruption on access to sexual and reproductive health and rights in Eastern and Southern Africa.

The Coronavirus disease 2019 (COVID-19) resulted in the disruption of Sexual and Reproductive Health Rights (SRHR) services in the Eastern and Southern Africa region. To date, studies estimating the impact of COVID-19 disruptions have mainly focused on SRHR services without estimating the economic implication. We used national service coverage data on the effectiveness of interventions from the lives saved tool (LiST), a mathematical modeling tool that estimates the effects of service coverage change in mortality. We computed years lost due to COVID-19 disruption on SRHR using life expectancy at birth, number of years of life lost due to child mortality, and life expectancy at average maternal death. We calculated the economic value of the lives saved, using the values of statistical life year for each of the countries, comparing 2019 (pre-COVID-19) to 2020 (COVID-19 era). The total life-years lost were 1,335,663, with 1,056,174 life-years lost attributed to child mortality and 279,249 linked to maternal mortalities, with high case-fatality rates in the Democratic Republic of Congo, Burundi, and Tanzania. The findings show COVID-19 disruptions on SRHR services between 2019 and 2020 resulted in US$ 3.6 billion losses, with the highest losses in Angola (USD 777 million), South Africa (USD 539 million), and Democratic Republic of Congo (USD 361 million). The monetized value of disability adjusted life years can be used as evidence for advocacy, increased investment, and appropriate mitigation strategies. Countries should strengthen their health systems functionality, incorporating and transforming lessons learned from shock events.

Features of modelling the components of the financial and economic stimulation system of the advanced technologies’ introduction of smart industrial development

The introduction of advanced technologies by the Industry 4.0 phase at national enterprises is in the initial stages and requires economic support from the state. The system of financial and economic stimulation for the introduction of advanced technologies for smart-industrial development should combine monetary (monetary and credit) and fiscal (tax and budget) incentives. To ensure the validity and optimality of the choice of the list of such measures, it is relevant to build scenarios for the development of national industry using economic and mathematical modelling tools that allow assessing the impact of the identified incentives on the overall economic growth indicators. An analysis of the models by areas of incentives aimed at studying the impact of incentives on the economic performance of enterprises, industry or the overall economy of the States is carried out. The advantages and disadvantages of the DCF, VAR and GARCH models are outlined, which, along with the methods for assessing the effectiveness of individual incentives CBA, ROI, NPV, etc., may require modification to consider individual incentives, the introduction of additional factors and the accumulation of variables to assess the overall impact on the economy. Therefore, they are labour-intensive for solving the outlined problems, but can be used for intermediate calculations for certain incentive areas. For modelling the components of the financial and economic stimulation system at the national level, the most appropriate models are general economic models (Cobb-Douglas model, Solow model, AD-AS model, Samuelson-Hicks model, etc.). The modified Cobb-Douglas model, taking into account the digitalisation factor, reflects the dependence of production on the introduction of advanced smart technologies, has a number of advantages over other models and is technically convenient for long-term calculations, which is required for national industry development scenarios to assess the impact of the introduction of financial and economic stimulation for industrial development. Promising areas of research are outlined.

FORECASTING OF THE MAIN SEGMENTS OF THE FINANCIAL MARKET OF UKRAINE

The article analyzes and builds economic and mathematical models for forecasting the main segments of the financial market of Ukraine:: the banking market; stock market; insurance market. The role of the financial market in modern civilized society is huge. Its functions include the mobilization of capital, its distribution among industries, control and support of the reproductive process, as well as increasing the efficiency of the economic system as a whole. The turning point for the Ukrainian financial market was 2022, namely the beginning of a full-scale Russian invasion, which led to the isolation of the financial market of Ukraine due to the introduction of martial law. In order to identify the key challenges for the development of the financial market, it is necessary to forecast the dynamics of its main segments using the tools of economic and mathematical modeling. A feature of the development of the domestic financial market is that the main part of the state’s financial resources is concentrated in such subjects of the financial system as deposit (commercial) banks; non-deposit financial intermediaries (insurance companies); subsidiary financial corporations (stock exchanges). According to the constructed forecasting models, it can be concluded that, all things being equal, in 2023 and 2024, the tendency to decrease the number of operating banks will continue and will be 59 and 54, respectively. As for the share of commercial banks with domestic capital, it will remain at the same level in 2023 and decrease by 4% in 2024. The number of insurance companies will decrease to 111 in 2023 and increase by 8 in 2024. Regarding the size of their assets, in 2023 there will be a decrease to the level of UAH 68,557 million, and a slight increase to the level of UAH 69,283 million in 2024. The share of the exchange market in the total volume of trades on the securities market will increase to 62% in 2022 and to 66% in 2023.

Improving the Efficiency of Fuel Combustion with the Use of Various Designs of Embrasures

Currently, NOX emission requirements for thermal power plants and power equipment are being tightened. Regime and technical measures are being developed to improve the efficiency of fuel combustion in boilers. Due to the high cost of field studies, and in some cases the impossibility of conducting them, mathematical modeling tools allow one to work out technical and tactical measures. In this paper, the multidisciplinary STAR-CCM+ platform with GMU-45 type burners is used to simulate the combustion of gaseous fuel in a digital model of an energy boiler of the type TGME-464. By conducting numerical experiments, the possibility of reducing NOX emissions by using flue gas recirculation is considered, and the efficiency of burner devices is compared when using different embrasure configurations.

Формирование системы индикаторов оценки агропромышленного потенциала региона в направлении его цифровой трансформации

Abstract. The development of the agro-industrial complex of the region in the conditions of the digital economy is impossible without a comprehensive assessment of the agro-industrial potential, on the basis of which reasonable management decisions will be made. The purpose is to identify the specifics of the agro-industrial potential of the region, and develop a system of indicators for its assessment in the context of the digital transformation of the agro-industrial complex. The solution of this issue is based on the use of modern tools of economic and mathematical modeling. The work also uses such research methods as generalization and synthesis, system analysis, modeling and optimization. Scientific novelty. A generalized method for assessing the agro-industrial potential in the direction of its digital transformation and an algorithm for determining the criterion for the economic growth of an agro-industrial complex subject when managing the development of its digital potential are proposed. Results. The main aspects of the analysis of the digital potential of the subject of the agro-industrial complex are identified, among which the key role of the resource potential, which differs in directions and purposes of use, is highlighted, which must be taken into account when developing management decisions. A model of the resource platform of the agro-industrial complex of the region, based on modern information and communication technologies, is proposed, the implementation of which will ensure effective management of the resource potential. A step-by-step scheme for analyzing the digital potential of an agro-industrial complex subject is presented, which makes it possible to identify its capabilities and performance indicators that reflect the level of development of the agro-industrial complex of the region. The necessity of increasing the information support of the management activity of a business entity in three areas is substantiated: improvement of resource management processes, optimization of their quality and volume, business process management. To determine the criterion for economic growth of individual subjects of the agro-industrial complex of the region, an algorithm is proposed that makes it possible to identify the sources and rates of such growth. The practical significance of the study lies in the development of a system of indicators that allow assessing the agro-industrial potential of the region in the direction of its digital transformation, on the basis of which the efforts of the state and investors will be directed to the implementation of measures to support and regulate the processes of digitalization of the industry.

Multisensor Data Fusion in IoT Environments in Dempster-Shafer Theory Setting: An Improved Evidence Distance-Based Approach.

In IoT environments, voluminous amounts of data are produced every single second. Due to multiple factors, these data are prone to various imperfections, they could be uncertain, conflicting, or even incorrect leading to wrong decisions. Multisensor data fusion has proved to be powerful for managing data coming from heterogeneous sources and moving towards effective decision-making. Dempster-Shafer (D-S) theory is a robust and flexible mathematical tool for modeling and merging uncertain, imprecise, and incomplete data, and is widely used in multisensor data fusion applications such as decision-making, fault diagnosis, pattern recognition, etc. However, the combination of contradictory data has always been challenging in D-S theory, unreasonable results may arise when dealing with highly conflicting sources. In this paper, an improved evidence combination approach is proposed to represent and manage both conflict and uncertainty in IoT environments in order to improve decision-making accuracy. It mainly relies on an improved evidence distance based on Hellinger distance and Deng entropy. To demonstrate the effectiveness of the proposed method, a benchmark example for target recognition and two real application cases in fault diagnosis and IoT decision-making have been provided. Fusion results were compared with several similar methods, and simulation analyses have shown the superiority of the proposed method in terms of conflict management, convergence speed, fusion results reliability, and decision accuracy. In fact, our approach achieved remarkable accuracy rates of 99.32% in target recognition example, 96.14% in fault diagnosis problem, and 99.54% in IoT decision-making application.

Predictable inventory management within dairy supply chain operations

PurposeWith the current wave of modernization in the dairy industry, the global dairy market has seen significant shifts. Making the most of inventory planning, machine learning (ML) maximizes the movement of commodities from one site to another. By facilitating waste reduction and quality improvement across numerous components, it reduces operational expenses. The focus of this study was to analyze existing dairy supply chain (DSC) optimization strategies and to look for ways in which DSC could be further improved. This study tends to enhance the operational excellence and continuous improvements of optimization strategies for DSC managementDesign/methodology/approachPreferred reporting items for systematic reviews and meta-analyses (PRISMA) standards for systematic reviews are served as inspiration for the study's methodology. The accepted protocol for reporting evidence in systematic reviews and meta-analyses is PRISMA. Health sciences associations and publications support the standards. For this study, the authors relied on descriptive statistics.FindingsAs a result of this modernization initiative, dairy sector has been able to boost operational efficiency by using cutting-edge optimization strategies. Historically, DSC researchers have relied on mathematical modeling tools, but recently authors have started using artificial intelligence (AI) and ML-based approaches. While mathematical modeling-based methods are still most often used, AI/ML-based methods are quickly becoming the preferred method. During the transit phase, cloud computing, shared databases and software actually transmit data to distributors, logistics companies and retailers. The company has developed comprehensive deployment, distribution and storage space selection methods as well as a supply chain road map.Practical implicationsMany sorts of environmental degradation, including large emissions of greenhouse gases that fuel climate change, are caused by the dairy industry. The industry not only harms the environment, but it also causes a great deal of animal suffering. Smaller farms struggle to make milk at the low prices that large farms, which are frequently supported by subsidies and other financial incentives, set.Originality/valueThis paper addresses a need in the dairy business by giving a primer on optimization methods and outlining how farmers and distributors may increase the efficiency of dairy processing facilities. The majority of the studies just briefly mentioned supply chain optimization.

The Application of Mathematical Modeling Tools in Optimizing the Purification Process of the Substance Oligohexamethyleneguanidine Hydrocitrate

The current investigation is dedicated to the use of mathematical modeling, particularly the method of multifactorial analysis of multi-criteria optimization (MAMO) in pharmaceutical development. During the investigation the algorithmic sequence was offered and the necessary tests were provided. The gained data was interpreted through MAMO. The possibility of using the MAMO for solving the applied problem of purifying the oligohexamethyleneguanidine hydrocitrate (OHMG-HC) that is considered to be as a pharmaceutical substance for formation of medicines. The dependencies of purifying conditions that have influence on the final impurities contents and the reasonability of using the suggested algorithm as a means of pharmaceutical development.

Gas dynamics of stationary supersonic gas jets with inert particles exhausting into a medium with low pressure

Issues related to the development of tools for mathematical modeling of stationary supersonic flows of an ideal compressible gas with inert particles are considered. A mathematical model is constructed that describes the flow of an inviscid compressible gas with inert particles in a jet flowing from an axisymmetric nozzle into a flooded space. Provided that the flow is supersonic along one of the spatial coordinates, the Euler equations are hyperbolic along this coordinate. For numerical calculations of the gas flow field, the finite volume method and the marching method are used. For integration over the marching direction, the three-step Runge–Kutta scheme is used. The procedure for calculating the flows includes the reconstruction of the values of the desired functions on the faces of the control volumes from the average values over the control volumes and the solution of the problem of the decay of an arbitrary discontinuity (the Riemann problem). The Lagrangian method of test particles is used to describe the dispersed phase. The effects of the reverse influence of particles on the flow of the carrier gas are not taken into account. The effects of viscosity and rarefaction of the gas flow are taken into account only when the gas interacts with particles. Calculation of the trajectories of inert particles is carried out in a known flow field of the carrier gas. The motion trajectories of discrete inclusions in jet flows with strong underexpansion are presented. The influence of the particle size and the coordinates of the particle entry point into the flow on the features of their transfer by the jet stream are discussed. Efficient means of numerical simulation of stationary supersonic flows of an ideal compressible gas with particles in nozzles and jets have been developed. The calculation results are of interest for studying supersonic gas suspension flows around bodies and for calculating oblique shock waves.

Stationary Analysis Fluid Model Driven by an Queue

A Fluid queue is a mathematical model used to describe fluid level in a reservoir subject to randomly determined periods of filling and emptying the system without interruption called a buffer, according to a randomly varying rate regulated by an external stochastic environment. Such fluid queues are used as a mathematical tool for modeling, for example, to approximate discrete models, model the spread of wildfires in ruin theory and to model high speed data networks, a router, computer networks including call admission control, traffic shaping and modeling of TCP and production and inventory systems. The fluid from the first phase (i.e, fluid output of the queue) goes to the second phase represents a buffer with a constant leak rate c. We always assume that service rate is greater than buffer, μ ˃ c. In this paper, a fluid queue driven by infinite queue with fixed –size batch arrivals. The generating function technique is used to obtain the expressions for steady-state distribution of both the buffer content and stationary state probabilities of background birth-death process. Hence, the performance measures are computed whereas the server utilization analysis and mean buffer content are investigated. . In addition, some numerical results are provided to illustrate the effect of various parameters on the distribution of the buffer content.

Preface

Based on a successful conference, the 2022 International Conference on Applied Mathematics and Digital Simulation, AMDS 2022, held virtually via Zoom from November 26-28th, 2022 in Beijing, due to the continuing impact of COVID-19, the contributions are the results of submissions from the conference participants. They provide readers with a broader view of mathematical, statistical and computational science methods, ideas and tools.There are 88 participants in AMDS 2022 online conference, in which the program includes 4 keynote reports (35 minutes), 38 oral presentations (12 mins+3 Q&A) included in two sessions (advances in mathematical modelling and theory, mathematical modelling and computation in engineering and physical sciences) and 10 E-posts. This conference emphasizes the development of theories and applications and promotes interdisciplinary endeavours among mathematicians, statisticians, scientists, engineers and researchers from other disciplines.This volume comprises select proceedings of AMDS 2022 of 48 papers from 75 submissions. All accepted manuscripts were peer-reviewed by 2 reviewers at least in a double-blind review process. A total of 51 reviewers participated in this conference, who provided their professional and strict comments for authors to ensure the topic and quality of the manuscripts. There are eight topic partitions, including mathematical modelling and theory, statistical modelling and data analysis, fluid dynamics and mechanics, intelligent control, machine learning, medical physics, mathematical modelling physical engineering, and optics and engineering. This proceeding constitutes an up-to-date account of principles, techniques, and tools for mathematical simulation & modelling in a wide range of research fields.List of Scientific Committee is available in this Pdf.

Enabling and centering equity and justice in clean energy transition research

Enabling and centering equity and justice in clean energy transition research

Mathematical Modeling and Software Tools for Breeding Value Estimation Based on Phenotypic, Pedigree and Genomic Information of Holstein Friesian Cattle in Serbia

In this paper, six univariate and two multivariate best linear unbiased prediction (BLUP) models were tested for the estimation of breeding values (BV) in Holstein Friesian cattle in Serbia. Two univariate models were formed using the numerator relationship matrix (NRM), four using the genomic relationship matrix (GRM). Multivariate models contained only an NRM. Two cases were studied, the first when only first lactations were observed, and the second when all lactations were observed using a repeatability model. A total of 6041 animals were included, and of them, 2565 had data on milk yield (MY), milk fat yield (FY), milk fat content (FC), milk protein yield (PY) and milk protein content (PC). Finally, out of those 2565 cows, 1491 were genotyped. A higher accuracy of BV was obtained when using a combination of NRM and GRM compared to NRM alone in univariate analysis, while multivariate analysis with repeated measures gave the highest accuracy with all 6041 animals. When only genotyped animals were observed, the highest accuracy of the estimated BV was calculated by the ssGBLUPp model, and the lowest by the univariate BLUP model. In conclusion, the current breeding programs in Serbia should be changed to use multivariate analysis with repeated measurements until the optimal size of the reference population, which must include genotyping data on both bulls and cows, is reached.

Electric Vehicles and the Use of Demand Projection Models: A Systematic Mapping of Studies

In today’s world, electric vehicles have become a real solution to the problem of pollution caused by petrol and diesel-powered vehicles. However, incorporating them successfully into the global vehicle park poses new challenges. Some of these challenges have to do with meeting the electricity demand, providing the physical installations for charging, and the size and capacity of the electric grid required to deliver the necessary supply. Solving these new problems requires determining or projecting the electrical and/or physical requirements involved, but there is no single model or methodology to do this, nor any single document which summarizes the existing information. To address this situation, this work presents the result of a systematic mapping study that seeks to provide organized information about the (mathematical) models for the demand arising from electric vehicles, as well as to answer a series of questions posed for this research. The results obtained show that there is a wide variety of models used to determine demand requirements –of either physical or electrical elements– in which mathematical modelling and operations research tools are normally used. Other results indicate that demand models are mainly focused on the electrical requirements rather than on physical ones, and that, in most cases, the type of vehicle for which the demand is studied is not mentioned.

Economic and Mathematical Modeling in Budgeting

The article is devoted to an overview of modern modeling approaches for effective management of enterprise budgets. The article examines the toolkit of economic and mathematical modeling that can be used in the budgeting system. It is proposed to increase the efficiency of the budgeting process by applying the tools of economic and mathematical modeling at the stages of budget development and resource allocation, as well as in the process of budget control and monitoring. To increase the clarity of the simulation procedure and results, a visualization of the TO BE model is presented in IDF0 notation (simulation language) on the Ramus platform. It is noted that the effectiveness of the budgeting system based on the use of economic-mathematical modeling tools will allow to improve resource expenditure planning taking into account the opportunities, priorities, needs and limitations of a specific enterprise and its external business environment. The need to implement digitalization tools and economic-mathematical modeling in the budgeting system is substantiated. The purpose of the article is to analyze the possibilities of forming an effective enterprise budgeting system based on the successful implementation of economic and mathematical modeling tools. The authors focus on the potential of using business analytics as a result of using economic and mathematical modeling tools to form an effective budgeting system. The article argues for the possibility of effectively using modeling tools in the budgeting process, which allows enterprises to make high-quality management decisions based on forecasts, scenarios, optimization recommendations, visualization of current problem situations, etc. The scientific novelty of this article lies in the fact that the recommendations and conclusions provided by the authors can be useful for domestic enterprises in the current conditions of severe restrictions on available resources, lack of free funds, existing and potential risks. In general, this article is useful for those who want to learn more about the possibilities of using economic-mathematical modeling tools in the budgeting system.

Prospects for the development and application of artificial intelligence technologies in Russia

The paper examines the prospects for the design and introduction of artificial intelligence technologies in Russia’s economic system. Based on official rankings of the globe’s leading organizations and the tools of economic and mathematical modeling, we have assessed the impact of artificial intelligence technologies on the level of competitiveness of the national economy. The obtained results indicate a rather strong impact of artificial intelligence technologies on the level of competitiveness of the national economy. We have also analyzed the current level of development of artificial intelligence technologies in the Russian Federation, and pointed out significant risks and threats caused by the introduction of these technologies. The development of artificial intelligence technologies can lead to the fact that, at some point, human capital might cease to be necessary in the economy; simply put, human capital will become an unnecessary factor in economic development. In order for humanity to cope with the challenges, driven by the development of artificial intelligence technologies, the implementation of intelligent information systems should not be thoughtless; their implementation should be reasonable and extremely careful. Furthermore, we suggest how to make the use of artificial intelligence technologies in Russia’s economy more efficient. The conclusion is that, first of all, Russia should develop artificial intelligence technologies in relation to the real sector of the economy in order to increase the competitiveness of domestic goods and services and achieve the goal of import substitution. Artificial intelligence technologies should aim at improving the performance of the public health service.

A Novel Method for Converting Colored Petri Nets to Ladder Diagram in the Automation of Automated Manufacturing Systems

The Ladder Diagram (LD) is an industry-standard programming language for constructing automated manufacturing systems (AMSs) control algorithms. Petri net (PN) theory, on the other hand, is a mathematical and graphical modeling tool for AMSs. Multiple types of PN-based LDs are designed for AMSs with highly complicated LD structures. Thus, it is necessary to propose a technique that can assist in the minimization of the structural complexity of LDs. The main purpose of this study is to propose a methodology for the implementation of LDs in AMSs. First, a colored resource-oriented Petri net (CROPN) is developed for modeling and guaranteeing the deadlock-free behavior of AMS. Second, a ladder diagram CROPN (LDCROPN) is constructed in order to transform the CROPN into an LD. The proposed LDCROPN is assessed using instances from the literature. The results show that the LDCROPN is effective, has a simpler structure, and has less computational overhead than existing techniques.

Nonlinear mathematical model of an economic soliton

In modern conditions of economic transformation, the functioning and development of production systems is characterized by instability, nonlinearity and dynamism of the main indicators and parameters. The financial and production system is affected by a large number of market, inflationary, social and other disturbances, which leads to the losses in financial stability, a decrease in production volumes, a decrease in demand for manufactured products, etc. Therefore, it is necessary to have an effective management system and operational decision-making. The relevant direction for solving this problem is the development of a flexible intelligent control system that makes it possible to diagnose quickly the unfavorable state of the financial and production system and activate promptly the mechanisms that return the system to equilibrium. In this case, information becomes the main resource of management, which performs an integrating role and is a necessary component when using all other resources. All this predetermines the use of information technology management. With a high dynamism and instability of the external environment, it becomes necessary to apply the methods and approaches of the new science of management, concentrating its attention on the theory of complex systems and nonlinear dynamics, with the help of which complex control systems can cope effectively with uncertainty and rapid changes. The development and use of modern information technologies for enterprise management are based on the introduction of integrated information processing technology and the creation of mathematical methods and computer modeling tools. In the work of information technologies, management is implemented by creating an integrated intelligent computerized system based on the use of economic and mathematical methods, computer technology and communication means, i.e. implements a fundamentally new management platform, which is based on the integration of management information through a mechanism for generalizing the information database and knowledge.

The Reaction of the Legislature to the Initiation of an Excessive Deficit Procedure. The Example of Poland in 2004–2008 and 2009–2015

Accession to the European Union means that each Member State must comply, under the community treaties that have been adopted, with several principles and numerous operating standards, among which one can distinguish the maintenance of public finance discipline at a sufficiently low level. An instrument supporting the preservation of an adequate balance of public finance is the so-called excessive deficit procedure. Poland was subjected to the excessive deficit procedure in two periods: 2004–2008 and 2009–2015. The article employs a unique research methodology to establish long-term trends in law creation, based on the theory of supply and demand. In particular, this text focuses on the question of whether a certain law was intended to increase or decrease the costs of performing state functions. It demonstrates through the use of the tools of mathematical modeling that the excessive deficit procedure applied to Poland not only had an impact on state finances, but also had a long-term effect on the legislature, which consistently created regulations aimed at reducing public expenditure. The paper underlines the significance of sustainable public finances for macroeconomic stability, using Poland as a case study. Despite the beneficial impact of the excessive deficit procedure in reducing Poland’s public debt, the research uncovers a recurring pattern of increasing public spending after improving financial stability.

MODERN TOOLKIT FOR PROVIDING THE USE OF REAL ESTATE AT THE REGIONAL LEVEL

The relevance of the formation of modern tools for ensuring the use of real estate at the regional level has been proven. As a result of the research, the goal of determining the modern toolkit for the formation and use of real estate at the regional level has been achieved. To achieve the goal, the following tasks were solved: substantiation of theoretical provisions regarding the definition of real estate at the regional level; characteristics of methods and models affecting the level of real estate use. A modern toolkit for the formation and use of real estate at the regional level is proposed, which consists of methods and models, mechanisms, which made it possible to propose measures to increase the efficiency of the use of real estate objects and land resources. As a result of the research, the categorical apparatus for determining real estate was improved, the distinguishing feature of which is the inclusion of land plots, other objects located on it, forming a spatial provision from above and below, determined by a long-term nature, the movement of which leads to a violation of its functional features. A method of integral assessment of the level of real estate use of regions was developed, which is based on a set of expert and analytical methods, local, systemic, integral models, a multi-level system of indicators, which made it possible to form the basis for mathematical modeling of factors of real estate use at the regional level.The proposed model of the influence of the integral indicator of the use of real estate at the regional level on the index of the gross regional product through the use of mathematical modeling tools, which made it possible to form a quantitative basis for ensuring positive trends of the generalizing factor of regional development. Methodical approaches to the assessment of real estate use have been developed, which are based on methods and models that characterize the directions and features of the application of spatial, functional, investment, environmental support, which provide the opportunity to form a mathematical basis and to single out the appropriate tools for developing a method of assessing the level of real estate use in regions. Mathematical modeling of the processes of real estate use at the regional level was carried out on the basis of establishing relationships between systemic spatial, functional, investment, environmental factors and an integral indicator. A mechanism for the use of real estate at the regional level was developed, which is based on the results of assessment, mathematical modeling, and forecasting of the factors of real estate use, which made it possible to determine the directions for the implementation of scientifically based recommendations and to build geospatial monitoring maps.