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Soft Computing in Economics

Soft Computing in Economics
155-1305/01
čeština Soft Computing in Economics
155-1305/02
čeština Soft Computing in Economics
155-1305/03
čeština

Summary

The aim of the course is to understand and use stochastic and intelligent SC methods in economics for modeling and construction of flash predictions for economic and financial processes. These methods are based on supervised, unsupervised and hybrid learning from data, development of novel ANN architectures and design of novel systems for business applications. Students will be able to discuss and evaluate the performance of intelligent information processing in comparison with probabilistic computation.

Literature

SAINI, N. Review of Selection Methods in Genetic Algorithms, International Journal
of Engineering and Computer Science, 2017, vol. 6, no. 12, pp. 22261-22263.
CHARU C. Aggarwal. Neural Networks and Deep Learning. Springer International Publishing AG, 2018,ISBN 3319944622 .

Advised literature

CHARU C. Aggarwal. Neural Networks and Deep Learning. Springer International Publishing AG, 2018,ISBN 3319944622 .
SAINI, N. Review of Selection Methods in Genetic Algorithms, International Journal
of Engineering and Computer Science, 2017, vol. 6, no. 12, pp. 22261-22263.


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Language of instruction čeština, čeština, čeština
Code 155-1305
Abbreviation SCE
Course title Soft Computing in Economics
Coordinating department Department of Applied Informatics
Course coordinator dr hab. Maria Antonina Mach-Król