KDnuggets 99:20, item 10, Courses:

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Date: Fri, 17 Sep 1999 13:43:50 +0200
From: Saso Dzeroski Saso.Dzeroski@ijs.si
Subject: Analysis of environmental data, 8-11 Nov 1999, Ljubljana, Slovenia

ANALYSIS OF ENVIRONMENTAL DATA WITH MACHINE LEARNING METHODS
8.-11. November 1999, Ljubljana, Slovenia

http://www-ai.ijs.si/SasoDzeroski/aep/aep.html

Organized by Jozef Stefan Institute, Ljubljana,
in cooperation with University of Ljubljana and Nova Gorica Polytechnic

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, such as modeling algal growth in lakes and lagoons,
analysing the influence of physical and chemical parameters on selected
bioindicator organisms, and predicting the biodegradability of chemical
compounds. 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 machine learning methods and tools introduced are
applicable to data analysis problems from different areas.

The seminar is intended for researchers and other professionals in the areas
of biology, chemistry, environmental science, and other areas related to
ecology and environmental management, whose work requires the analysis of
environmental data or modeling ecological processes.

Contents
   * Introduction to machine learning
        o Bayesian classification
        o Neural networks
        o Instance-based learning (nearest neighbor classification)
        o Learning decision (classification) and regression trees
        o Learning classification rules
        o Machine discovery of equations
        o Inductive logic programming
   * An overview of environmental applications of machine learning
        o Analysis of the influence of environmental factors on respiratory
          diseases
        o Analysis of the influence of soil habitat features on the
          abundance of Collembola
        o Modeling phytoplankton growth
        o Modeling interactions among red deer population, meteorological
          parameters and new forest growth
   * Case studies of using machine learning to analyse ecological data
        o Analysis of water quality data (Slovenian and English rivers)
        o Modeling algal growth in the Lagoon of Venice
        o Predicting biodegradability of chemical compounds
        o Runoff prediction from rainfall and past runoff
   * Demonstrations/practical work with machine learning software packages
     on real ecological data and individual consultations with lecturers

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