ANALYSIS OF ENVIRONMENTAL DATA
WITH MACHINE LEARNING METHODS

Environmental data often need to be analysed in order to obtain information necessary for environmental management decisions. Sometimes it is necessary to use the data to build a model of the environmental process that we want to manage. In other cases the analysis is necessary to understand the environmental processes studied by identifying and understanding the interrelationships of different parameters.

Machine learning can be used to elicit regularities from data. In comparison to simple forms of regularities/dependencies treated by statistical methods, machine learning methods can find more complex regularities/dependencies that include both numerical and logical conditions.

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.

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

• Professor Ivan Bratko , Faculty of computer and information sciences, University of Ljubljana and
  Jozef Stefan Institute, Ljubljana
  
• Dr. Saso Dzeroski, Jozef Stefan Institute, Ljubljana
  
• Dr. Boris Kompare, Faculty of civil engineering and geodesy, University of Ljubljana
  
• Professor William J. Walley, School of Computing, Staffordshire University, Stafford, UK

Registrations will be taken until the course fills up on a first-come first-served basis. Please register as soon as possible: due to the practical exercises the number of participants is limited.
The registration fee for the seminar is 440 USD. It includes access to the lectures, demonstrations and hands-on work, seminar materials, lunches and refreshments. It also includes 6.5% VAT.

Payment should be done by bank transfer or check. Please send receipt of payment or check made out to:

   Jozef Stefan Institute
   Jamova 39
   1000  Ljubljana, Slovenia

   through NOVA LJUBLJANSKA BANKA d.d., Trg republike 2,
           1520 Ljubljana, Slovenia
   on account no.: 50100-620-133-900-27620-840(USD)-3237/9
   S.W.I.F.T.: LJ BA SI 2X

   reason of payment AED COURSE

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