Risk Analysis and Management
Code | Completion | Credits | Range | Language |
---|---|---|---|---|
D32RAM | ZK | Czech |
- Garant předmětu:
- Tomáš Janda, Jiří Šejnoha
- Lecturer:
- Tomáš Janda, Jiří Šejnoha
- Tutor:
- Supervisor:
- Department of Mechanics
- Synopsis:
-
1. Terminology
2. Theory - Probability and mathematical statistics, Reliability
3. Risk analysis/assessment
- Hazard identification
- Risk quantification
- Tools and numerical methods
- Classical statistical inference
- Bayesian inference
- Monte Carlo methods
4. Risk management
- Decision analysis
- Utility theory in decision analysis
- Requirements:
-
The elementary knowledge of differential and integral calculus is welcomed. Basic experience with programing is also welcomed since all examples are provided in Python.
- Syllabus of lectures:
-
1. Basic relations and terminology
2. Common probability distributions
3. Transformation of random variables
4. Reliability of simple structures
5. Processes evolving in time
6. Solution methods and models
7. Markov chains and Kolmogorov equations
8. Monte Carlo method, Latin Hypercube sampling
9. Advanced methods: Subset simulation, MCMC sampling
10. Bayesian inference, Metropolis Hastings algorithm
- Syllabus of tutorials:
-
Hands-on exercises are integrated into lectures.
- Study Objective:
- Study materials:
-
David Vose, Risk Analysis: A Quantitative Guide, 3rd Edition, Wiley, 2008
Michael Rees, Business Risk and Simulation Modelling in Practice Using Excel VBA and RISK, Wiley, 2015
- Note:
- Time-table for winter semester 2024/2025:
- Time-table is not available yet
- Time-table for summer semester 2024/2025:
- Time-table is not available yet
- The course is a part of the following study plans: