Course Details

Artificial inteligence methods in water management

DS76 course is part of 4 study plans

Ph.D. full-t. program nD > VHS compulsory-elective Winter Semester 2nd year 8 credits

Ph.D. combi. program nDK > VHS compulsory-elective Winter Semester 2nd year 8 credits

Ph.D. full-t. program nDA > VHS compulsory-elective Winter Semester 2nd year 8 credits

Ph.D. combi. program nDKA > VHS compulsory-elective Winter Semester 2nd year 8 credits

Problems of uncertainty in rainfall-runoff modelling, stochastic processes, vague description of variables, adaptivity principle, learning systems, application of artificial neural networks, application of fuzzy models, application of genetic algorithms

Course Guarantor

prof. Ing. Miloš Starý, CSc.

Institute

Institute of Landscape Water Management

Prerequisites

Hydrology, hydraulics, mathematics, probability theory and mathematical statistics, physics

Planned educational activities and teaching methods

Teaching methods depend on the type of course unit as specified in the article 7 of BUT Rules for Studies and Examinations.

Objective

Application of basic methods of artificial inteligence in hydrology and water management

Specification of controlled instruction, the form of instruction, and the form of compensation of the absences

Vymezení kontrolované výuky a způsob jejího provádění stanoví každoročně aktualizovaná vyhláška garanta předmětu.

Lecture

3 hours/week, 13 weeks, elective

Syllabus of lectures

1. Problems of uncertainty in hydrology and water management
2. Adaptivity principle and learning systems
3.-4. Neural networks and their simulators
5.-7. Application of neural networks on selected problems solutions
8.-9. Fuzzy models
10.-11. Application of fuzzy models
12.-13. Genetic algorithms and their application