Description:
Applications of reliability theory include the assessment of system and equipment reliability, failure analysis, and forecasting. Technological failures and operator errors are assessed to help improve safety and optimize operational processes.

Description:
Probabilistic modeling of meteorological extremes, climate change impacts, and rare events is performed using advanced statistical analysis, extreme value theory, and data integration methods.

Description:
Risk and uncertainty analysis helps assess system security, model sensitivity, and data uncertainty. This service allows you to identify risk scenarios, reduce their likelihood, and make effective, data-driven decisions.

Description:
AI, data analytics, and data science services, including task automation, predictive modeling, natural language processing, computer vision, recommendation systems, big data analysis, optimization, risk and fraud detection, and the creation of customized solutions, are provided.

Description:
Smart information integration tools are being developed and applied for the synthesis of data from different sources, the aggregation of expert knowledge, and the automated modeling of information flows.

Description:
Analysis of the uncertainty and sensitivity of modeling results helps to assess the accuracy of models, identify parameters that influence results, and define the limits of forecast reliability for more accurate risk assessment and better decision-making.

Description:
Failure and longevity data are analyzed, and system reliability, uncertainty, and sensitivity of results are evaluated. This helps identify risk factors, predict failures more accurately, and optimize maintenance and operational decisions.