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Ukončeno v akademickém roce 2018/2019

GeoComputation

Type of study Follow-up Master
Language of instruction English
Code 548-0083/03
Abbreviation GC
Course title GeoComputation
Credits 5
Coordinating department Department of Geoinformatics
Course coordinator prof. Ing. Jiří Horák, Dr.

Osnova předmětu

The course is focused on the introduction to the theory of fuzzy sets and their application in practice. Then, foundations of the theory of decision making in a situation without risk and in a situation with risk are discussed. Second half of the course is devoted to the fractal and chaos theory.

Povinná literatura

AWANGE, J.M., PALÁNCZ, B., LEWIS, R.H., VOLGYESI, L. Mathematical geosciences. Springer Berlin Heidelberg, New York, NY, 2017.
BRAMER, M.A. Principles of data mining. Springer, London, 2020.
KANEVSKI M. F., Poudnoukhov A., Timonin V. Machine learning for spatial environmental data. CRC Press 2009. 377 s., 978-0-8493-8237-6
ZAKI, M.J., MEIRA, W. Data mining and machine learning: fundamental concepts and algorithms. Cambridge University Press, Cambridge, United Kingdom, 2020; New York, NY.

Doporučená literatura

BRUNTON, S.L., KUTZ, J.N. Data-driven science and engineering: machine learning, dynamical systems, and control. Cambridge University Press, Cambridge, 2019.
DAUPHINÉ, André. Fractal Geography. Wiley, 2012. ISBN 978-1-84821-328-9.
KANEVSKI M. F. Advanced mapping of environmental data : geostatistics, machine learning and Bayesian maximum entropy. ISTE 2008. 313 s., 978-1-84821-060-8
MILLER H. J., HAN J. Geographic Data Mining and Knowledge Discovery. Chapman & Hall/CRC, 2009.