548-0083/02 – GeoComputation (GC)

Gurantor departmentDepartment of GeoinformaticsCredits5
Subject guarantordoc. Ing. Jiří Horák, Dr.Subject version guarantordoc. Ing. Jiří Horák, Dr.
Study levelundergraduate or graduateRequirementChoice-compulsory
Year1Semestersummer
Study languageEnglish
Year of introduction2015/2016Year of cancellation
Intended for the facultiesHGFIntended for study typesFollow-up Master
Instruction secured by
LoginNameTuitorTeacher giving lectures
HOR10 doc. Ing. Jiří Horák, Dr.
IVA026 doc. Ing. Igor Ivan, Ph.D.
LAM05 doc. RNDr. Marek Lampart, Ph.D.
Extent of instruction for forms of study
Form of studyWay of compl.Extent
Full-time Credit and Examination 2+2
Part-time Credit and Examination 6+6

Subject aims expressed by acquired skills and competences

The objective is to learn student how to use basic methods of artificial intelligence namely machine learning such as decision trees, support vector machines and neural analysis in geoinformatics, explain them pronciples and methods of data mining, theory of chaos and fractals, and selected methods of stochastic spatial simulations.

Teaching methods

Lectures
Tutorials

Summary

The subject introduces basic approaches and methods of artificial intelligence, especially machine learning and focus on their utilization in geoinformatics, where it is necessary to evaluate spatial properties, to adapt spatial sampling, and perform appropriate data transformation. Classification methods such as Bayes classifiers, decision trees, support vector machines. Variants for regression analysis. Neural network, including advanced methods such as deep learning and convolution neural network. The further part demonstrates problems and methods of data mining, detection of patterns, sequences and association rule mining, basic techniques of text mining and clustering methods. Introduction to chaos theory and fractals, utlization in geoinformatics. Stochastic spatial simulations.

Compulsory literature:

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.

Recommended literature:

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., Poudnoukhov A., Timonin V. Machine learning for spatial environmental data. CRC Press 2009. 377 s., 978-0-8493-8237-6 MILLER H. J., HAN J. Geographic Data Mining and Knowledge Discovery. Chapman & Hall/CRC, 2009.

Way of continuous check of knowledge in the course of semester

E-learning

Other requirements

No additional requirements are imposed on the student.

Prerequisities

Subject has no prerequisities.

Co-requisities

Subject has no co-requisities.

Subject syllabus:

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.

Conditions for subject completion

Part-time form (validity from: 2017/2018 Winter semester)
Task nameType of taskMax. number of points
(act. for subtasks)
Min. number of points
Credit and Examination Credit and Examination 100 (100) 51
        Credit Credit 33  17
        Examination Examination 67  18
Mandatory attendence parzicipation:

Show history

Occurrence in study plans

Academic yearProgrammeField of studySpec.ZaměřeníFormStudy language Tut. centreYearWSType of duty
2021/2022 (N3654) Geodesy, Cartography and Geoinformatics (3608T002) Geoinformatics P Czech Ostrava 1 Choice-compulsory study plan
2021/2022 (N3654) Geodesy, Cartography and Geoinformatics (3608T002) Geoinformatics P English Ostrava 1 Choice-compulsory study plan
2021/2022 (N3654) Geodesy, Cartography and Geoinformatics (3608T002) Geoinformatics K Czech Ostrava 1 Choice-compulsory study plan
2020/2021 (N3654) Geodesy, Cartography and Geoinformatics (3608T002) Geoinformatics K Czech Ostrava 1 Choice-compulsory study plan
2020/2021 (N3654) Geodesy, Cartography and Geoinformatics (3608T002) Geoinformatics P English Ostrava 1 Choice-compulsory study plan
2020/2021 (N3654) Geodesy, Cartography and Geoinformatics (3608T002) Geoinformatics P Czech Ostrava 1 Choice-compulsory study plan
2019/2020 (N3654) Geodesy, Cartography and Geoinformatics (3608T002) Geoinformatics P English Ostrava 1 Choice-compulsory study plan
2019/2020 (N3654) Geodesy, Cartography and Geoinformatics (3608T002) Geoinformatics P Czech Ostrava 1 Choice-compulsory study plan
2019/2020 (N3654) Geodesy, Cartography and Geoinformatics (3608T002) Geoinformatics K Czech Ostrava 1 Choice-compulsory study plan
2018/2019 (N3654) Geodesy, Cartography and Geoinformatics (3608T002) Geoinformatics P Czech Ostrava 1 Choice-compulsory study plan
2018/2019 (N3654) Geodesy, Cartography and Geoinformatics (3608T002) Geoinformatics P English Ostrava 1 Choice-compulsory study plan
2018/2019 (N3654) Geodesy, Cartography and Geoinformatics (3608T002) Geoinformatics K Czech Ostrava 1 Choice-compulsory study plan
2017/2018 (N3654) Geodesy, Cartography and Geoinformatics (3608T002) Geoinformatics P Czech Ostrava 1 Choice-compulsory study plan
2017/2018 (N3654) Geodesy, Cartography and Geoinformatics (3608T002) Geoinformatics K Czech Ostrava 1 Choice-compulsory study plan
2017/2018 (N3654) Geodesy, Cartography and Geoinformatics (3608T002) Geoinformatics P English Ostrava 1 Choice-compulsory study plan
2016/2017 (N3654) Geodesy, Cartography and Geoinformatics (3608T002) Geoinformatics P English Ostrava 2 Choice-compulsory study plan
2015/2016 (N3654) Geodesy, Cartography and Geoinformatics (3608T002) Geoinformatics P English Ostrava 2 Choice-compulsory study plan

Occurrence in special blocks

Block nameAcademic yearForm of studyStudy language YearWSType of blockBlock owner