Conditions Of Uncertainty Research Articles

Auditor's professional judgment and opinion

The paper is devoted to such an actual problem in the field of audit activity as professional judgment and an auditor's opinion. A proper clarification of the logical content of these concepts significantly affects the effectiveness of the audit according to requirements of International Standards on Auditing (ISA). To date, in scientific publications the various approaches to the interpretation of the given concepts are expressed. A significant part of the authors is limited to general definitions and only some of them make attempts to substantiate their research with the laws and categories of logic. At the same time, native authors in every possible way avoid a full-fledged logical definition of content of the concept "auditor's opinion". The main reason is that there is an unsuccessful translation from English terminology into Ukrainian. In some cases, the term "opinion" has been translated as "opinion", and in others it has been called "conclusion". Therefore, if the term "opinion" is preferred, it turns out that the audit begins with an auditor's opinion and ends with it. An auditor's opinion fully encompasses such forms of logical thinking as concepts, judgments and inferences. The paper not only shows the misinterpretation of the concepts of "professional judgment" and "auditor's opinion" in a number of scientific studies. Also it is proposed the own vision of the cognition process in the auditing field based on the laws of general and dialectical logic. A related scheme of an auditor's professional judgment is given. From this scheme it can be seen that the opinion of a professionally competent auditor from the very beginning of the audit is being transformed through rationale into the concepts and requirements of the ISA. Further, an auditor's rationale is being transformed into judgments and conclusions. Based on them, as a result of proving or proving and planning, the specific conclusions of an auditor are formed as a report. The paper states that an auditor's professional judgment, like the professional judgment of other specialists, is subordinated to the general laws of logic. Its specificity lies in the fact that it is carried out with professional skepticism in conditions of uncertainty and risk and is subject to the requirements of legislation and ISA.

Исследование модернизации морского пассажирского порта на основе цифрового двойника и оценка инфраструктуры с помощью динамических данных от беспилотных авиационных систем

The current state of the maritime passenger transportation industry is considered, as well as the factors influencing the chosen industry are investigated (competition between ports in the sea region, new environmental requirements and a shortage of space for new ports and terminals in megacities). Models of the evolution of seaports and terminals in the regions of the seas are analyzed and the need to solve the problem of forecasting development, reasonable modernization is revealed infrastructure. The importance of integrating passenger ports into urban transport systems and ensuring effective interconnection of maritime transport with regional transport systems is noted. Special attention is paid to the growth and development potential of sea ferries and cruises in the Baltic Sea region, the historical importance of St. Petersburg for cruise tourism and the need for the gradual restoration of the port and the development of new route networks are noted. The necessity of developing new methods for modernizing the infrastructure of passenger seaports based on the creation of digital models and the use of dynamic data is substantiated. As a solution, it is proposed to create a new digital model of a marine passenger port using information obtained from unmanned aircraft systems. This model will accurately take into account the infrastructural features of passenger ports and terminals, as well as the established priority of berths for the service of cruise and ferry ships. For multi-scenario modeling, a new digital model of the marine passenger port of St. Petersburg “Marine Façade” is proposed. To analyze the simulation results, the developed software modules in the Python programming language are proposed to describe the behavior strategies of the decision maker (port manager). To describe the decision-making process in the conditions of uncertainty that arises when making a decision on the modernization of the port infrastructure, the choice of the Wald criterion was justified as a criterion. A series of experiments was performed, based on the data, digital 2D and 3D models of a marine passenger port were formed for subsequent use in the AnyLogic environment, and a digital twin was built. A distinctive feature of the model is the up-to-date information on the state of the transport infrastructure and integration with data on ship calls. The presented model, methods of working with the results of multi-dimensional modeling, the use of unmanned aircraft systems, and the development of a model based on decision-making under uncertainty can be applied to other passenger seaports and terminals, which emphasizes the universality of the proposed approach.

KONTROL SLIDING MODE ADAPTIF DENGAN VAKSINASI DAN TREATMENT PADA MODEL PENYEBARAN TUBERKULOSIS

This research examines the design of adaptive sliding mode control in a tuberculosis (TB) disease spread model, considering uncertainties within the model. The TB model involves five state variables (susceptible individuals, vaccinated individuals, individuals with latent TB infection, individuals with active TB infection, and individuals under treatment) and three control input variables consisting of vaccination and treatment. The objective of this control design is to reduce the number of susceptible individuals, individuals with active TB infection, and the number of individuals under treatment by tracking the given reference functions. Stability and convergence of tracking errors of the controlled system are proved using the Lyapunov Stability Theorem. Numerical simulations are conducted to evaluate the performance of the designed control under various parameter uncertainty conditions. Based on the simulation results, it is shown that the adaptive sliding mode controllers guarantee the convergence of tracking errors is achieved despite the presence of uncertainty in the model.

Управление образовательным процессом субъектов креативных индустрий

The article delineates a number of characteristic features in managing the educational process within the realm of creative industries. They are defined according to the essential features of the key concepts “educational process management” and “subjects of creative industries”. They encompass a range of common traits, including issues of management organization levels, functions, methods, principles, etc. The fundamental distinctions of these components are predominantly shaped by the specific nature of creative industries subjects’ activities in the educational sphere, which typically unfold non-linearly and under conditions of high risk, uncertainty, and complexity in predicting outcomes. This is a sphere of activity oriented towards systemic innovation implementation, seeking and utilizing opportunities to satisfy human desires and needs through the realization of unique educational products, including those in the realm of additional education for both children and adults. The outcome here entails the creation, promotion, and dissemination and/or implementation of creative products in the field of additional education. In conclusion, the management of educational processes in creative industries requires a nuanced understanding of the unique challenges and opportunities inherent in this domain. By leveraging flexible and adaptive management strategies, educators and industry stakeholders can foster creativity, innovation, and collaboration, thereby enriching the educational experience and driving positive outcomes for all stakeholders involved. Further research is needed to explore specific management approaches and interventions tailored to the evolving needs of creative industries education.

The uncertainty of quantum states with respect to the projective measurement

The uncertainty relation is a distinctive characteristic of quantum theory. The uncertainty is essentially rooted in quantum states. In this work we regard the uncertainty as an intrinsic property of quantum state and characterize it systematically with respect to given projective measurement. Some basic concepts about uncertainty are reformulated in this context. We prove and get the form of the uncertainty preserving operations. The quantum states with maximal uncertainty are characterized. A universal decomposition of uncertainty into classical uncertainty and quantum uncertainty is provided. Furthermore, a unified and general relation among uncertainty, coherence and coherence of assistance is established. These results are independent of any explicit uncertainty measure. At last, we propose a new uncertainty measure called the geometric uncertainty based on the fidelity and link it with the geometric coherence.

Robust-augmentation nonlinear dynamic inversion control of over-actuated coaxial high-speed helicopter in transition mode

As the elevator and rudder can be used actively for control, in addition to the rotors, Coaxial High-speed Helicopters (CHHs) have the problems of control redundancy and changing control authority in the transition mode. This paper presents a robust-augmentation transitioning flight control design for a CHH under the adverse conditions of parametric uncertainties and external disturbances. First, based on control characteristic analysis, an Adaptive Filtered Nonlinear Dynamic Inversion (AFNDI) controller is proposed for the angular rate to handle the effect of unknown unstructured uncertainties and external turbulence. Theoretical analysis proves that the presented angular rate controller can guarantee steady-state and transient performance. Furthermore, the attitude angle and velocity controllers are also added. Then, an Incremental-based Nonlinear Prioritizing Control Allocation (INPCA) method is designed to take into account control surface transition and changing control authority, which efficiently distributes the required moments between coaxial rotors and aero-surfaces, and avoids the control reversal problem of the yaw channel. In the proposed control architecture, the low-pass filter is introduced to alleviate the adverse influence of time delay and measurement noise. Finally, the effectiveness of the proposed controller is demonstrated through nonlinear numerical simulations, and is compared with existing methods. Simulation results show that the proposed control law can improve both capabilities of disturbance rejection and fast response, and works satisfactorily for the CHH transitioning control characteristic.

Urban influence on convective precipitation in the Paris region: Hectometric ensemble simulations in a case study

AbstractThe purpose of this study is to investigate the influence of the urban environment of the Paris region on an isolated convective cell that formed downwind of the city on May 7, 2022, using the Meso‐NH research atmospheric model at a horizontal scale of 300 m. To account for all sources of forecast uncertainty, the initial and lateral boundary conditions of the simulations are provided by an ensemble prediction system. A multi‐layer urban scheme is used to represent the influence of buildings on the airflow accurately. Two sets of ensemble simulations are performed: the first set (URB) uses a fine‐scale surface description of the city, while the second set (NOURB) replaces urban surfaces with vegetation. This sensitivity test shows that, despite the high variability of simulated precipitation within the ensemble, the city of Paris plays a statistically significant role in the initiation of convection in this case. Convective cells are initiated over the city for several members of the URB ensemble, while almost no precipitation is simulated for the same members of the NOURB ensemble. The mean 6‐h rainfall accumulation of the URB ensemble is increased by 70% over Paris (compared with the NOURB ensemble) and no statistically significant trend is found around the city. The analysis reveals that the capital experiences a higher sensible heat flux due to drier and warmer air, resulting in enhanced vertical velocities and an increase in boundary‐layer height in the URB ensemble. Additionally, the total water content and cloud fraction over Paris are intensified, leading to more precipitation. These findings suggest that urbanisation has a notable impact on convection and precipitation processes in this case.

Автоматическое построение элементов представления процедурных знаний подводным интеллектуальным роботом в условиях недоопределенности

В статье рассматриваются и решаются проблемы, связанные с развитием одного из подходов к построению модели представления процедурных знаний интеллектуального робота в виде заданного набора фрейм-микропрограмм поведения. В общем случае фрейм-микропрограммы представляют собой навыки поведения, связанные с решением соответствующих им подзадач безотносительно к конкретной предметной области, обеспечивающие роботу возможность автоматического формирования планов целенаправленной деятельности, связанных с решением сложных задач в различных условиях проблемной среды. Иначе говоря, фрейм-микропрограммы поведения являются “кирпичиками”, на основе которых интеллектуальный робот может конструировать сложные планы целенаправленной деятельности в различных условиях функционирования. В развитие данной модели представления процедурных знаний робота предложена структура фрейм-микропрограммы поведения, в результате декомпозиции которой можно получить модули, определяющие относительно простые навыки поведения. Такой подход позволяет роботу организовать либо более гибкий процесс планирования целенаправленной деятельности в недоопределенных проблемных средах, либо обеспечить интеллектуального робота возможностью автоматического построения недостающих для достижения заданной цели типовых элементов представления процедурных знаний. Выбор конкретного из данных двух способов использования полученных в результате разбиения фрейм-микропрограмм поведения модулей зависит от сложности решаемой интеллектуальным роботом задачи и размерности семантической сети, описывающей текущую ситуацию проблемной среды. Определены условия, обеспечивающие выбор результативных модулей представления знаний в процессе планирования целенаправленной деятельности и автоматического построения недостающих для вывода решений фрейм-микропрограмм поведения. Показано, что предложенный подход к построению модели представления процедурных знаний и инструментальных средств их обработки в процессе планирования целенаправленной деятельности позволяет повысить когнитивные возможности интеллектуальных роботов и на этой основе обеспечить решение сложных задач в недоопределенных проблемных средах. The article discusses and solves problems associated with the development of one of the approaches to constructing a model for representing the procedural knowledge of an intelligent robot in the form of a given set of behavioral frame-microprograms. In general, frame microprograms represent behavioral skills associated with solving the corresponding subtasks, without reference to a specific subject area, providing the robot with the ability to automatically generate plans for goal-directed activities related to solving complex problems in various environmental conditions. In other words, frame-microprograms of behavior are the “building blocks” on the basis of which an intelligent robot can construct complex plans for purposeful activity in various operating conditions. In development of this model for representing a robot's procedural knowledge, a structure of a frame-microprogram is proposed, as a result of the decomposition of which it is possible to obtain modules that define relatively simple behavioral skills. This approach allows the robot to organize either a more flexible process of planning purposeful activities in underdetermined problem environments, or to provide the intelligent robot with the ability to automatically construct typical elements of procedural knowledge representation that are missing to achieve a given goal. The choice of a particular one of these two methods of using the modules obtained as a result of splitting the behavioral frame-microprograms depends on the complexity of the task being solved by the intelligent robot and the dimension of the semantic network describing the current situation of the problem environment. The conditions have been determined to ensure the identification and selection of effective knowledge representation modules in the process of planning targeted activities and the automatic construction of behavioral frame-microprograms that are missing for the conclusion of decisions. It is shown that the proposed approach to constructing a model for representing procedural knowledge and tools for processing it in the process of planning purposeful activities makes it possible to increase the cognitive capabilities of intelligent robots and, on this basis, provide solutions to complex problems in underdetermined problem environments.

Impact of sentiment tendency of media coverage on corporate green total factor productivity: The moderating role of environmental uncertainty

In the context of China's carbon neutrality goal and increasing environmental responsibilities, this study examines the impact of media sentiment on Corporate Green Total Factor Productivity (GTFP), especially considering environmental uncertainty. Utilizing data from the CNRDS financial news database and employing the non-radial SBM-ML index to assess GTFP, the research explores how positive, neutral, and negative media coverage influences corporate sustainability behaviors. Results indicate that positive media coverage significantly enhances GTFP during corporate growth and maturation phases by improving public perception and investor confidence. In contrast, negative media coverage tends to reduce GTFP, particularly under conditions of high environmental uncertainty, highlighting the challenges during vulnerable periods. This study contributes to understanding the nuanced effects of media sentiment on corporate sustainability practices and underscores the importance of managing media relations strategically according to corporate lifecycle stages and environmental contexts to optimize sustainability outcomes. The findings offer valuable insights for businesses to align their media strategies with sustainability goals and for policymakers to develop regulations that harness media influence to support corporate environmental accountability. By strategically managing media narratives and fostering a supportive policy environment, corporations can leverage the power of media to drive their sustainability agendas and contribute to the achievement of national and global environmental targets.

A probabilistic framework to evaluate seismic resilience of substations based on three-stage uncertainty

Electrical substation systems exhibit vulnerability after an earthquake. It results in significant economic losses because of the uncertainty of the functional state and recovery process. To quantitatively assess the uncertainty of substations, this paper proposes a probability-based seismic resilience assessment framework. This framework considers uncertainty in three stages: functional state, functional recovery, and resource constraints. Based on the functional characteristics of substation systems, a directed acyclic graph was constructed, and the Monte Carlo algorithm was used to obtain the functional state matrix, thereby establishing a probability-based functional state model. Moreover, a dynamic post-earthquake functional recovery analysis framework was built based on recovery efficiency metrics, and functional recovery paths were obtained through iterative simulations. A stepped functional recovery curve was developed based on resource constraints. Three-stage uncertainty parameters were transformed into resilience features for quantitative assessment. By analysing seismic resilience of a typical 220 kV step-down substation, probability distributions of functional recovery curves and confidence intervals for seismic resilience metrics were obtained. Notably, mutual constraint relationships among resource conditions were identified.

Robotic Manipulator in Dynamic Environment with SAC Combing Attention Mechanism and LSTM

The motion planning task of the manipulator in a dynamic environment is relatively complex. This paper uses the improved Soft Actor Critic Algorithm (SAC) with the maximum entropy advantage as the benchmark algorithm to implement the motion planning of the manipulator. In order to solve the problem of insufficient robustness in dynamic environments and difficulty in adapting to environmental changes, it is proposed to combine Euclidean distance and distance difference to improve the accuracy of approaching the target. In addition, in order to solve the problem of non-stability and uncertainty of the input state in the dynamic environment, which leads to the inability to fully express the state information, we propose an attention network fused with Long Short-Term Memory (LSTM) to improve the SAC algorithm. We conducted simulation experiments and present the experimental results. The results prove that the use of fused neural network functions improved the success rate of approaching the target and improved the SAC algorithm at the same time, which improved the convergence speed, success rate, and avoidance capabilities of the algorithm.

Economic Analysis of High-Speed Railways: A Holistic Methodological Approach

The most controversial issue regarding a high- speed railway investment is the huge capital cost, and the main question is whether its benefits will be worth the huge investment costs. High-speed railways have long planning processes and face great risks. Therefore, a holistic approach has been required under conditions of uncertainty. The purpose of this paper is to unify the methods for determining the huge rail investment costs. This paper investigated the economic analysis of high- speed railways as a part of a new silk iron road corridor, in terms of both passenger and freight railway transport between Europe and Asia. In this context, a benefit-cost evaluation of the Ankara-Sivas high-speed railway as a part of the backbone railway line of Turkey's Edirne- Kars high-speed railway corridor has been carried out. A holistic methodological method is presented for evaluating the benefit-cost analysis of both high-speed and freight railways. The economic analysis results show that in cross-continental countries, network effects must be taken into consideration when evaluating the high- speed railway's benefit-cost analysis.

Exploring the role of Dynamic Presencing in a group coaching training context for fostering transformative leadership development in disruptive times.

With the growing array of challenges humanity has been experiencing since the global pandemic, knowledge workers at all levels of organizations are experiencing a noted increase in the volatility, uncertainty, complexity, and ambiguity (VUCA) conditions of their work and lives. This has brought about significant changes in ways of working and associated ways of being that have become more fragmented and virtual. Disruptive change continues to unfold on many levels of society, from the organizational to the individual level, with multiple and often unintended consequences. This article outlines how the body of work of Dynamic Presencing in a group coaching context facilitates responsive forms of personal development as well as a deeper transformation of one's leadership identity in the face of such change, which in turn serves as an approach that can be useful in navigating VUCA conditions that are becoming increasingly prevalent. The transformative process of Dynamic Presencing develops core inner leadership capabilities with a noted increase in the quality of internal and interpersonal forms of self-,presence-, and presencing-awareness. Overall, Dynamic Presencing serves as a critical enabler of presencing mastery, which instills deeper confidence and resourcefulness in working with the VUCA conditions of our global world by deepening our presencing process and refining our methods for inner leadership development in turbulent times.

Simulation of decision-making processes regarding the formation of an invest-ment portfolio using IT

Significant changes observed in the global economy and in particular in Ukraine in recent years have significantly increased interest in the problems of investment theory. An example of this is the intensification of trading in shares of large and medium-sized international companies and cryptocurrencies, which causes a rapid increase in their values. It is known that in the theory of investments, the task of optimizing the set of components of investment portfolios is considered as a special case. As you know, the issue of decision-making regarding the formation and optimization of an investment portfolio is in the field of attention both for large investment companies and for private investors, since when choosing among possible alternatives for the distribution of capital investments within the market of financial assets, the investor will receive different results. As a result, it is necessary to understand the amount of income received during the period of ownership of the investment portfolio. It is known, according to Gary Markowitz's theory of investment risk, that the optimal distribution of the filling of the investment portfolio should provide the best income while maintaining the lowest risks. At the same time, the decision regarding the structure of capital distribution is often made in conditions of uncertainty, and the profitability of investing capital in investment objects is of a random nature. Since uncertainty creates additional risks, the investment of capital and the task of optimizing the investment portfolio must be considered and solved in the presence of risk. At the same time, effective investment activities require the use of special mathematical methods and informational tools to support decision-making. In the article, using the Ruby programming language, a model is proposed that can be used in the decision-making process when forming a set of components of a portfolio of securities, which allows potential investors to independently assess the effectiveness of a set of investment portfolios by comparing the growth dynamics of shares available on the financial market. It is known that most of the information an investor encounters is in a tabular format, and according to the methodology of scientific knowledge, a person better perceives visualized ways of presenting information. The model proposed in the work uses visualization tools built into the software product, which presents available tabulated information in a structured graphic form.

Particle Swarm Optimization-Based Model Abstraction and Explanation Generation for a Recurrent Neural Network

In text classifier models, the complexity of recurrent neural networks (RNNs) is very high because of the vast state space and uncertainty of transitions, which makes the RNN classifier’s explainability insufficient. It is almost impossible to explain the large-scale RNN directly. A feasible method is to generalize the rules undermining it, that is, model abstraction. To deal with the low efficiency and excessive information loss in existing model abstraction for RNNs, this work proposes a PSO (Particle Swarm Optimization)-based model abstraction and explanation generation method for RNNs. Firstly, the k-means clustering is applied to preliminarily partition the RNN decision process state. Secondly, a frequency prefix tree is constructed based on the traces, and a PSO algorithm is designed to implement state merging to address the problem of vast state space. Then, a PFA (probabilistic finite automata) is constructed to explain the RNN structure with preserving the origin RNN information as much as possible. Finally, the quantitative keywords are labeled as an explanation for classification results, which are automatically generated with the abstract model PFA. We demonstrate the feasibility and effectiveness of the proposed method in some cases.

THE ROLE OF ARTIFICIAL INTELLIGENCE IN THE DEVELOPMENT OF THE COMPANY'S BUSINESS PROCESSES

Doing business in the conditions of globalization and rapid changes requires from entrepreneurs constant development and adaptation, search for new ideas and use of advanced technologies. Active competition and functioning in conditions of uncertainty require the formation of new competitive advantages, effective management of business processes and digital awareness. The aim of the paper is the systematization of the key approaches to implementation of artificial intelligence in business processes of the company and assessment of its influence on business results Empirical research uses quantitative methodology. Secondary data is collected from surveys and reports of leading world consulting companies. Within the framework of the research, the essence and key directions of artificial intelligence development were studied. Analysis of the use of artificial intelligence in company’s business processes was conducted. The positive cases of artificial intelligence implementation were considered, the influence of AI solutions on the development of modern organizations was determined. Advantages and disadvantages of AI solutions for business were considered.

FEATURES OF COPING STRATEGIES IN CONDITIONS OF UNCERTAINTY OF WARTIME

Relevance. The purpose of this article is to empirically investigate the discrepancies in the selection of coping strategies among groups of people during war under various conditions of uncertainty. Methodology. The sample consists of 186 residents of Ukrainian cities who live under various conditions of uncertainty. Methods: author’s questionnaire, methods: «Test for psychological diagnostics of coping mechanisms (E. Heim)», «The Intolerance of Uncertainty Scale (IUS-12) (N. Carleton, adaptation by H. Gromova)»; mathematical methods for processing empirical data using the IBM SPSS Statistics 26 package. Results. Respondent groups, based on their location relative to the front line, show statistically significant discrepancies in cognitive and behavioral coping strategies. The empirical study’s analysis showed that individuals living in the front and near-front zones often compare their problems with others and downplay their difficulties more frequently (41,94%) than those living further from the front line (21.94%). Furthermore, individuals closer to the front line show a higher tendency to employ the adaptive coping strategy «altruism» (19.35%), that is, they offer help to others in overcoming difficulties more often than those living further from the front line (6.45%). Both groups predominantly employ relatively adaptive coping strategies. However, a divergence in problem-solving approaches exists: individuals in the front and near-front zones typically avoid problem-solving by engaging in a favorite activity, whereas the other group tends to evade problem-solving by resorting to alcohol, medicines, sedatives, or indulging in tasty food. The study did not identify statistically significant differences between groups regarding intolerance to uncertainty.

Charitable and Volunteer Activities as a Social Practice: Legal, Teleological and Axiological Aspects

Charitable and Volunteer Activities as a Social Practice: Legal, Teleological and Axiological Aspects

The value of scenario discovery in land-use modeling: An automated vehicle test case

Long-range planning is an uncertain endeavor. This is especially true for urban regions, small ships in a global urban storm that are too small to influence macro policies and without the land-use powers of local governments. Exploratory scenarios, the established practice for planning under deep uncertainty, have inspired stakeholders to consider multiple futures but have fallen short of identifying robust and contingent policies. We need new tools to plan under conditions of deep uncertainty. Scenario discovery is a technique for using simulation models to explore the performance of policy options across uncertain scenarios. This paper presents an application of scenario discovery in land-use modeling and asks what this computationally intensive approach offers relative to a more circumscribed exploration of uncertainty space. The introduction of autonomous vehicles (AVs) and their associated impacts on land use provide a test case demonstrating this method, as well as a topic of substantive concern. This research concludes that scenario discovery is particularly valuable for identifying the conditions under which contingent policies are likely to succeed. In terms of AV policy, this research establishes that forward-thinking, transit-oriented-development strategies can mitigate spatial dispersion while also reducing overall housing costs. In addition, I find that AVs may blunt the impacts of some current policy tools if they extend the distance individuals are willing to travel to work.

The use of neural networks in the foresight process

The article considers scenarios of application of neural networks of different architectures to fulfill tasks in the foresight process. The purpose of the article is to determine at what stages of the foresight procedure the application of neural networks is justified and with what architecture. The differences between foresight and the process of forecasting are revealed. In addition, the concept of foresight, its main stages and phases, classification are considered. It is substantiated that the application of neural networks can significantly facilitate the foresight procedure at such stages as collection and processing of primary information, development of scenarios and solutions to problems, communication, and report preparation. It is shown that different types of neural networks are suitable for different foresight tasks. It is revealed that neural networks can process a larger amount of data and automatically detect complex patterns, which makes them more effective under conditions of environmental uncertainty and variability. The article ephasises the importance of further research and development of methods for applying neural networks in foresight processes with consideration to the specifics of particular industries and types of tasks. In the course of the research, the authors used analytical methods of diagnostics, establishing cause-and-effect relationships, etc.