Multidimensional prediction of heterogeneous electromechanical systems for risk management based on fuzzy temporal ontological and cognitive models
Problem definition: The energy, technical and operational characteristics of heterogeneous electromechanical systems (HEMS) change significantly during their operation. The complexity of HEMS prediction negatively affects the quality of risk management. The topological approach to the complex study of HEMS is the basis for the development of intellectual methods, models and technologies for the research of HEMS (predictive analytics, condition diagnostics, resource and risk assessment). This approach indicates the expediency of combining fuzzy ontological and cognitive models for complex analysis and multidimensional prediction of HEMS. Fuzzy ontological modeling provides an interoperable representation and complex analysis of HEMS. Fuzzy cognitive models allow prediction of HEMS. The aim of the research is to implement the proposed approach to the joint use of fuzzy temporal ontological and cognitive models for complex analysis, multidimensional prediction and risk management of HEMS. Methods used: topological approach to HEMC research; fuzzy ontological engineering; fuzzy cognitive modeling; fuzzy and soft measurements and computing. Novelty: An approach to multidimensional prediction of NEMS for risk management based on a combination of original fuzzy temporal ontological and cognitive models is proposed. Result: The complex problem of representation, multidimensional forecasting and risk management of EMS has been solved through the joint use of fuzzy temporal ontological and cognitive models. Practical significance: The practical significance of the results lies in improving the accuracy of HEMS prediction and the quality of risk management.