I received this through the European Society for Ecological Modelling and
felt it might be of general interest to list members, particularly those
already in Europe:
You are cordially invited to attend the seminar on
ANALYSIS OF ENVIRONMENTAL DATA WITH MACHINE LEARNING METHODS
17. - 21. March 2008, Ljubljana, Slovenia
http://www-ai.ijs.si/SasoDzeroski/aep/aep.html
Organized by the Jozef Stefan Institute, Ljubljana,
in cooperation with the Jozef Stefan International Postgraduate School
and the University of Nova Gorica
The seminar will give an introduction to selected machine learning methods
as well as illustrative case studies of using these methods to analyse
environmental data.
Applications in the areas of aquatic ecosystems, agriculture, forestry,
environmental epidemiology, and disaster forecasting/relief will be covered
in
detail.
The participants will learn to use selected machine learning tools
and will have the opportunity for practical work with these tools on real
environmental data.
The seminar is intended for researchers and other professionals
whose work requires the analysis of environmental data
or modeling of ecosystems and ecological processes.
The seminar is intended for an audience with a diverse background,
and has been in the past attended by particpants coming from
the areas of biology, chemistry, environmental science,
and other areas related to ecology and environmental management,
as well as computer science and information technology,
The machine learning methods and tools introduced are applicable to
data analysis problems from different areas of environmental science and
management,
as well as data analysis problems from other areas.
For graduate students of institutions that participate in the ECTS,
including the Jozef Stefan International Postgraduate School
and the School of Environmental Sciences, University of Nova Gorica,
the seminar counts as regular coursework.
Contents
* Machine learning methods and methodology
o Machine learning, data mining and knowledge discovery
o Decision trees
o Classification rules
o Naive Bayes
o Nearest neighbor
o Evaluating classifiers
o Ensemble methods
o Feature weighting, ranking, and selection
o Equation discovery
o Automated modeling of dynamic systems
* Application areas
o Aquatic ecosystems
o Agriculture
o Forestry
o Environmental epidemiology
o Disater forecasting and relief
* Case studies of using machine learning to analyse ecological data
o Modeling algal growth in lakes and lagoons
o Modeling gene-flow between GM and conventional crops
o Predicting forest properties using remote sensing data
o Investigating the effects of mercury on miners
o Predicting danger of fire in the natural environment
... and many more
* Demonstrations/hands-on exercises/practical work
with a machine learning software package
on real ecological data and individual consultations with lecturers
* Participant presentations and discussion
Detailed schedule at http://www-ai.ijs.si/SasoDzeroski/aep/mar08sch.txt
