FI:P069 Hybrid Systems of Machine Lear - Course Information

P069 Hybrid Systems of Machine Learning

Extent and Intensity

2/1. 3 credit(s) (plus extra credits for completion). Recommended Type of Completion: zk (examination). Other types of completion: k (colloquium), z (credit).

Teacher(s)

doc. Ing. Jan Žižka, CSc. (lecturer)

Guaranteed by

prof. PhDr. Karel Pala, CSc.
Department of Machine Learning and Data Processing – Faculty of Informatics
Contact Person: doc. Ing. Jan Žižka, CSc.

Timetable

Thu 16:00–17:50 B411, Thu 18:00–19:50 A104

Course Enrolment Limitations

The course is also offered to the students of the fields other than those the course is directly associated with.

fields of study / plans the course is directly associated with

• Informatics (programme FI, B-IN)
• Informatics (programme FI, M-IN)
• Upper Secondary School Teacher Training in Informatics (programme FI, M-IN)
• Upper Secondary School Teacher Training in Informatics (programme FI, M-SS)
• Information Technology (programme FI, B-IN)

Syllabus

• Hybrid neural networks, a fuzzy perceptron, an AND/OR fuzzy neuron with t-norms and s-norms. Fuzzy neural networks.
• NEFCON and ANFIS architectures of hybrid neural networks. Neuro-fuzzy classifiers. Optimization of fuzzy rules by neural networks and genetic algorithms.
• Genetic algorithms and simulated annealing combined with neural networks, optimization of neural networks. Nonlinear dynamical systems, chaos, strange attractors. Recurrent networks, Hopfield networks.
• Applications of decision trees to the setup of neural network weights.
• Fuzzy-genetic modelling. Genetic programming.
• Application examples.

Language of instruction

Czech

• Enrolment Statistics (Spring 2001, recent)
  
• Permalink: https://is.muni.cz/course/fi/spring2001/P069