Course detail

Applied hydrology

FAST-DS64Acad. year: 2024/2025

Problems of uncertainty in hydrology, learning and adaptive systems, methods of artificial intelligence, artificial neural networks and their applications, fuzzy models and their applications, fuzzy regulators, qualitative and semi-qualitative models, genetic algorithms and their application

Language of instruction

Czech

Mode of study

Not applicable.

Guarantor

prof. Ing. Miloš Starý, CSc.

Department

Institute of Landscape Water Management (VHK)

Entry knowledge

Knowledge of hydrology, runoff control from river basin with the use of reservoirs and water management systems, mathematics (magister study level)

Rules for evaluation and completion of the course

Extent and forms are specified by guarantor’s regulation updated for every academic year.

Aims

Overview of possibilities of artificial intelligence use and other non traditional methods from hydrology and water management
Doktorand gains knowledge for applikation stochastic hydrology and operative hydrology methods in thesis

Study aids

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

Edited by Quentin Grafton: Water Resorces Planning and Management. Cambridge University Press 2011
Chow Ven Te: Handbook of Applied Hydrology. Published by McGraw Hill Text 1964

Recommended literature

Ram S. Gupta: Hydrology and Hydraulic Systems. Waveland Press 2007

Type of course unit

 

Lecture

39 hod., optionally

Teacher / Lecturer

prof. Ing. Miloš Starý, CSc.

Syllabus

1. Problems of uncertainty in hydrology, learning and adaptive systems, methods of artificial intelligence 2.-4. Artificial neural networks and their applications 5.-6. Fuzzy sets, fuzzy models 9.-10. Fuzzy regulators and their applications 11. Neural-fuzzy regulators and their application 12. Qualitative and semi-qualitative models 13. Genetic algorithms and their application