SubjectsSubjects(version: 953)
Course, academic year 2023/2024
  
Computational Intelligence Methods - N500013
Title: Metody výpočetní inteligence
Guaranteed by: CTU in Prague, Faculty of Information Technology (500)
Faculty: University of Chemistry and Technology, Prague
Actual: from 2021
Semester: winter
Points: winter s.:4
E-Credits: winter s.:4
Examination process: winter s.:
Hours per week, examination: winter s.:2/1, C+Ex [HT]
Capacity: unknown / unknown (unknown)
Min. number of students: unlimited
State of the course: cancelled
Language: Czech
Teaching methods: full-time
Teaching methods: full-time
Level:  
Is provided by: M500003
Guarantor: Kordík Pavel doc. Ing. Ph.D.
Is interchangeable with: M500003
Examination dates   Schedule   
Annotation -
Students will understand methods and techniques of computational intelligence that are mostly nature-inspired, parallel by nature, and applicable to many problems. They will learn how these methods work and how to apply them to problems related to data mining, control, intelligen games, optimizations, etc.
Last update: Jirát Jiří (10.01.2014)
Aim of the course -

Students will be able to:

Understand basic methods and techniques of computational intelligence that stem from the classical artificial intelligence

Apply them in knowledge engineering.

Last update: Jirát Jiří (31.01.2014)
Literature -

R:Konar, A. ''Computational Intelligence: Principles, Techniques and Applications''. Springer, 2005. ISBN 3540208984.

R:Bishop, C. M. ''Neural Networks for Pattern Recognition''. Oxford University Press, 1996. ISBN 0198538642.

Last update: Jirát Jiří (10.01.2014)
Learning resources -

https://edux.fit.cvut.cz/courses/MI-MVI/

(login necessary)

Last update: Jirát Jiří (10.01.2014)
Syllabus -

1. Introduction to computational intelligence, its uses.

2. Algorithms of machine learning.

3. Neural networks.

4. Evolutionary algorithms, evolution of neural networks.

5. [3] Computational intelligence methods: for clustering, for classification, for modeling and prediction.

6. Fuzzy logic.

7. Swarms (PSO, ACO).

8. Ensemble methods.

9. Inductive modeling.

10. Quantum and DNA computing.

11. Case studies, new trends.

Last update: Jirát Jiří (10.01.2014)
Registration requirements -

none

Last update: Jirát Jiří (31.01.2014)
Teaching methods
Activity Credits Hours
Účast na přednáškách 1 28
Práce na individuálním projektu 2.2 61
Účast na seminářích 0.5 14
4 / 4 103 / 112
 
VŠCHT Praha