Infopaket

Uncertainty and grouping of information

ОК.19

Обов’язкова дисципліна для ОП

Second

2023/2024

2 Semester

4

Know and understand the principles and methods of analysis and evaluation of tasks that contribute to the further development of effective use of information resources of decision-making systems.  

Full-time form

Know: data representation structures, their classification and clustering based on the use of mathematical methods and information systems and decision support systems. Be able to: formalize data presentation in conditions of uncertainty, apply in practice software tools for software design and development.

Fuzzy sets as a means of formalizing uncertainty. Review and application of methods of classification and clustering of informal data. Grouping on graphs. Clustering of computing resources in the creation and organization of information systems. Application of containerization and cloud technologies.

1. Orlovskiy S.A. Problemy prinyatiya resheniya pri nechetkoy iskhodnoy informatsii / S.A.Orlovskiy – M.: Nauka, 1981. – 206 p. 2. Kofman A. Vvedeniye v teoriyu nechetkikh mnozhestv / A.Kofman. — M.: Radio i svyaz', 1982. — 432 p. 3. Osovskiy S. Neyronnyye seti dlya obrabotki informatsii /S. Osovskiy. – M.: Finansy i statistika, 2002.– 344 p. 4. Ívokhín Ê.V. Odin metod klasterizatsíí̈ skladenikh nechítkikh mnozhin / Ê.V.Ívokhín, K.O.Kosins'kiy// Zhurnal obchislyuval'noí̈ ta prikl.matematiki. – 2007. – №2. – P.54-58. 5. Vyatchenin D.A. Nechetkiye metody avtomaticheskoy klassifikatsii/ D.A. Vyatchenin. - Minsk: Tekhnoprint, 2004. – 219 p. 6. Zaychenko YU.P. Nechetkiye modeli i metody v intellektual'nykh sistemakh /YU.P. Zaychenko. – Kiyev: Slovo, 2008. – 344 p. 7. Jamba M. Hierarchical cluster analysis and compliance / M. Jamba. - Moscow: Finance and Statistics, 1988. – 345 p.

Lecture, independent work.

Test work, test.

ukrainian