Yakubovska S. Models and methods of decision-making support in multiply connected object under conditions of uncertainty

The thesis is devoted to the study of intelligent decision support systems in determining and predicting the state of multiply connected objects.The thesis is devoted to the study of intelligent decision support systems in determining and predicting the state of multiply connected objects. In this paper, for the first time, a method for analyzing the state of multiply connected objects is proposed, which allows us to classify and predict the behavior of a multiply connected object in the state space under conditions of uncertainty. A feature of the proposed method is the ability to solve the problem of classifying objects based on the knowledge representation model at the first level, and at the second level - predicting their behavior in the state space, which improves decision-making efficiency in determining and predicting the state of a multiply connected object. Іn work are used methods of mathematical statistics (discriminant analysis) - for classification of the state of multiply connected object in conditions of uncertainty; methods of survival analysis and method verbal decision analysis (ordinal classification of states) - for the development of models for predicting the behavior of an object in the state space; methods of artificial intelligence (production model of presentation of knowledge) - for constructing a model of representing knowledge and creating a knowledge base of the intellectual decision support system.