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
Institute
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