This article considered the problem of determining the creditworthiness of an enterprise operating in the field of trade and services. The assessment of the creditworthiness of borrowers, particularly small businesses, needs to be more careful: the level of development of small enterprises and their specific activities must be considered, as well as the uncertainty in obtaining any financial result. A method for assessing the creditworthiness of enterprises (trade and services) is proposed, based on the use of the mathematical apparatus of the theory of fuzzy sets. This article analyzes the indicators of industry and regional specifics, indicators of the activity of a small enterprise, and financial and economic indicators typical for the service sector and trade. The rules on the basis of which decisions are made are formed in the form of logical formulas containing parameters. In its most general form, one parameter is predicted, called the creditworthiness index, which varies from 0 to 1 and has a natural interpretation. On the basis of the proposed method, examples of calculating the assessment of the creditworthiness of enterprises operating in the field of trade and services are given. The proposed scientific approach can be used as a basis for creating expert decision support systems for lending to small businesses.

We provide a nonlinear model of intersectoral balance with constant elasticity of substitution (CES) production functions of industries and CES utility function of final consumer for the study of intersectoral linkages in the Kazakhstan economy. The model is formalized in terms of the primal problem of resource allocation and the corresponding Fenchel dual problem which solution gives costs of inputs of industries in a supply network. We identify the model with the actual data of the Input-Output tables of Kazakhstan and estimate the elasticity of substitution of production factors for the aggregated industry complexes. With the help of developed framework, we evaluate the inter-industry financial flows in the aggregated supply network for the period 2013–2020 and compare the results with the actual data of Kazakhstan. The developed framework can be used to support decision-making processes in sustainable supply chain management in a situation of the government economic policy change and external shocks. Using the developed framework, we evaluate the risks for Kazakhstan’s supply chains in scenario of sharp weakening of the national currency.

This study investigates the integration of machine learning (ML) techniques into football analytics to predict player skills and optimize tactical decisions. A dataset of over 150,000 professional match actions from various leagues and seasons was analyzed using deep neural networks, convolutional neural networks (CNNs), and gradient boosting machines (GBM) algorithms on biometric, contextual, and match data. The valuing actions by estimating probabilities (VAEP) metric indicated scores from +1.8 to +3.0 for key players, enabling detailed performance evaluation. CNN models achieved up to 91% precision, 88% recall, and a receiver operating characteristic – area under the curve (ROC-AUC) of 0.94, confirming their effectiveness in predicting player actions and contributions. Injury risk prediction using eXtreme gradient boosting (XGBoost) reached an F1-score of 0.87 and a ROC-AUC of 0.92, offering actionable insights for injury prevention and optimal player rotation. The findings highlight artificial intelligences (AI)’s capacity to support individualized preparation, tactical adjustments, and cost-effective recruitment strategies. While computational demands and data quality remain challenges, the results demonstrate the transformative potential of AI in modern football, providing a practical framework for data-driven decision-making to enhance team performance and strategic planning

Задача факторизации характерна для широкого спектра математических задач. Решение многих математических задач связано с тем, что результат разложения чисел известен заранее. Данная работа посвящена исследованию задач факторизации с применением эллиптических кривых. Возможность использования таких структур, как эллиптические кривые, с целью факторизации придала новый импульс поиску решения этой проблемы. В статье рассмотрены основные проблемы метода эллиптических кривых, который основан на построении псевдокривой, и возможные пути его оптимизации. Исследованы соотношения между числом сгенерированных кривых и необходимой границей базового метода эллиптических кривых. Исследование данной проблемы выполнено с помощью программной реализации метода, на основе описанного алгоритма для чисел, делители которых не превышают пяти десятичных знаков. Результаты этого исследования представлены для различных случаев начального предела. Полученные результаты указывают на зависимость затрачиваемого времени, конечной границы при процессе факторизации и количества кривых, используемых во время факторизации, от количества кривых после которого увеличивается граница метода эллиптических кривых. В результате анализа этого метода, проведено исследование количества случаев получения делителей составного числа, с помощью дискриминанта кривой

Kazakhstan is one of the few countries in the world rich in oil, deservedly called“black gold” because it is the most important source of energy. The relevance of the studyof this paper is determined by the fact that the management of the oil industry affects notonly the management process itself, but also the social aspects of the implementation of thedevelopment strategy of the state as a whole. It is necessary to identify aspects of managementactivity and define criteria by which it is possible to calculate the effectiveness of managerialdecision-making in the analyzed industry. Agent models allow us to identify the main criteriafor the effectiveness of managerial decision-making and optimize social and economic costsfor their implementation within the framework of interdepartmental planning. The novelty ofthe research is determined by the fact that agent models are based not only on the associatedparameters of the management process, but also affect the possibility of planning currentactivities for a long period. The article shows that the formation of agent models should affectboth the aspect of the formation of matrices of complex managerial actions and calculationson the accounting of competencies in making managerial decisions. The practical significanceof the study is determined by the fact that the development of complex models based onagent forms allows expanding the use of forms of control over the industry by the state andother stakeholders. The implementation of a matrix form of management is proposed, takinginto account balanced industry indicators of management quality.