DENVI doctoral candidates and other doctoral candidates for whom the subject is relevant.
After completing the course, doctoral candidates will be familiar with the subject area of the course
To be completed at any time during doctoral studies, the course will be offered annually.
Environmental management problems are typically laden with different types of uncertainties arising from various sources. Decision analysis can be used to support decision making under uncertainty. A graphical Bayesian Network (BN) is a probabilistic model for causal inference and decision analysis. BNs can integrate qualitative and quantitative data in the same analysis, still providing numerical estimates and indicators about the system in focus. The approach can help with problem framing and structuring, and aid in diagnostic analysis of your system of interest, but it can also be utilized for predicting and divergent optimization tasks, for example for finding optimal management strategies.
The first part of the course will cover the principles of the BNs and provide examples about their use in environmental systems and decision analysis. The second part of the course is reserved for building students’ own models, so we encourage you to bring your own data and/or research question with you.
At least 90% compulsory attendance required.
Presentation of your own model (Friday afternoon).
According to the course content.
Although the course is taught on all days except Thursday in a computer classroom, you are advised to bring your own laptop with you. If this is not possible, please contact the teachers well in advance.