Course: Bayesian Belief Networks

29 Sep 2018
11:00 - 12:30
SR 113

Course: Bayesian Belief Networks

Bayesian Belief Networks for Integrated Ecological Modelling to Assess Communities and Ecosystem Services

Lecturers
Peter Goethals, PhD, Ghent University, contact: peter.goethals@ugent.be
Marie Anne Eurie Forio, PhD, Ghent University, contact: marie.forio@ugent.be

Brief description of the course content
The course aims at giving insights into the strengths and potential applications of BBN
networks to model and analyze species distributions, communities as well as ecosystem
services. The course is aimed at participants with basic ecological and modelling knowledge,
but even participants with limited computer background should be able to follow. Every
aspect of the hands-on exercises is learned from scratch, and no experience is needed with
programming or particular software packages. Slides, texts and databases will be on-line
disseminated at the start of the course.

Important is to bring a laptop, preferably will a loaded battery, on which the free version of
Netica is installed. You can download this software for free here. Versions are available for both Windows as Mac.

Schedule 11h-12h30
In the second part, an introduction will be provided of the Netica software that will be used
during the hands-on training part. This second part will consist of the introduction of the
main features in the software, and in particular how a BBN model can be setup from scratch
(introducing the variables and their linkages), and be linked to a database. Some short
exercises will allow the participants to make themselves familiar with these functions. After
that, also the model evaluation, sensitivity analyses and simulation options will be
introduced. The morning session will end with the introduction of the exercises.
• Netica software: advantages and main features
• BBN network development: introducing variables, class allocations and relations, and
linking a BBN network to a database
• Hands-on part to get familiar with the basic functions in the software
• Model evaluation, sensitivity analyses and making simulations: introduction and
short hands-on exercises
• Introducing the exercises of the afternoon session