Опис навчальної дисципліни

The subject of the course is models and algorithms of fuzzy inference. The issues of construction and use of fuzzy neural networks, systems, and algorithms of fuzzy inference are considered. The algorithms of data mining and processing of approximate information in fuzzy decision-making systems are considered.

Goal: systematized presentation of the theory, methods, tools, and basics of designing information systems based on fuzzy models and hybrid neural networks and methods of their application in decision-making systems.

Objectives: to familiarize students with models and algorithms of fuzzy inference, to acquire skills in building and using fuzzy neural networks, methods, and algorithms for their training, to learn about algorithms for data mining and processing expert information in decision-making systems.

According to the requirements of the educational and professional program, the student must

know modern methods and algorithms for building fuzzy models and hybrid neural networks; methods and algorithms for learning and self-learning; and methods of recognition and classification using hybrid neural networks.

be able to use modern fuzzy models, methods, and tools of fuzzy modeling in decision-making systems, in particular in the tasks of classification, modeling, and forecasting of complex processes.