Fractal-cluster technology for assessing the reliability of the information potential and digital entropy parameters of energy companies

Methods. The results were obtained using the following methods: fractal-cluster modeling – to identify hierarchical relationships between information resources and their impact on enterprise sustainability; multidimensional statistics methods – to group indicators and identify hidden dependencies; scenario modeling – to predict the impact of digital entropy on the functioning of an energy enterprise in a coherent digital environment. Results. In the context of the digital transformation of the economy, a key challenge for enterprises is to ensure the reliability and consistency of information flows, which directly affects the quality of management decisions and the sustainability of business processes. The problem lies in the lack of effective tools for a comprehensive assessment of the reliability of the information potential of energy companies in the context of growing digital entropy and the need to ensure information coherence. It is shown that the growth of digital entropy leads to data chaos, complicates their verification and integration into a single information space, which is especially critical for energy companies with a high level of technological complexity. Novelty. A fractal-cluster technology for assessing the reliability of information potential is proposed, combining fractal analysis methods and clustering algorithms. Fractal dimension is used as a quantitative indicator of structural complexity and the level of hidden chaos in information data, while the cluster approach provides systematic grouping of information components according to the criteria of completeness, accuracy, relevance, and coherence. This allows for the formation of an integral indicator of the reliability of an enterprise's information potential. A methodology for determining digital entropy parameters is proposed, which makes it possible to establish a relationship between the level of information chaos and the digital coherence of an enterprise. The scientific novelty of the work lies in the formation of a universal tool for assessing the reliability of the information potential and parameters of digital entropy of energy enterprises, which integrates quantitative and qualitative characteristics into a single analytical space and can be used both for strategic monitoring and for operational management of the information potential of energy enterprises. Practical value. Practical testing on energy companies showed that using a fractal-cluster approach makes the diagnosis of unreliable data more accurate, helps in lowering digital entropy, optimizes information resources, and boosts a company's digital coherence. The results obtained are of practical importance for the formation of information security systems, improving management efficiency, and ensuring the digital resilience of enterprises in conditions of digital entropy.