• S20: Data Mining as a Tool for Environmental Scientists

    Page: Main.S20 - Last Modified : Sun, 29 Jun 08

    Organisers

    Karina Gibert, KEMLG, Technical University of Catalonia, Catalonia (contact: karina.gibert@upc.edu)
    Miquel Sànchez-Marrè, KEMLG, Technical University of Catalonia, Catalonia
    Joaquim Comas, Laboratory of Chemical and Environmental Engineering, University of Girona, Catalonia
    Ioannis Athanasiadis, Istituto Dalle Molle di Studi sull'Intelligenza Artificiale, Lugano, Switzerland
    Joaquín Izquierdo Grupo Multidisciplinar de Modelación de Fluidos, Universidad Politécnica de Valencia, Spain
    Geoffrey Holmes, Department of Computer Science, University of Waikato, Waikato, New Zealand

    Topics

    • Applications of Data Mining Techniques to Environmental Domains
    • Interaction between AI and Statistic techniques for DM of Environmental Domains
    • The role of the Preprocessing and postprocessing in the whole Data Mining process
    • Software available

    Description

    This session is strongly linked with W4 (DM-TES08, 2nd iEMSs Workshop) and aims to approach and to promote the interaction between the Environmental Sciences community to the Data Mining community and related fields, such as Artificial Intelligence, Statistics or other fields to discuss the contribution of Data Mining techniques to Knowledge Discovery in Environmental Sciences, as well as to make data mining techniques more accessible to environmental modellers and to give data miners and developers a better idea of the needs and desires of the environmental community. The workshop will introduce interested parties to a range of data mining techniques and a selection of software packages. We also invite presentations of interesting applications of data mining to environmental problems. New or improved techniques or methods are welcome, as well as innovative applications.

    Schedule

    Wednesday 9
    Time Title Authors Place
    9:50 - 10:10 'Monolith2 - An On-line Database for Cement/Waste Products' M. O’Shea, J.A. Stegemann and M. Levene A6103
    10:10 - 10:30 'Coupling empirical and deterministic models to assess surface water contamination' M.Terrado, M.P. Lavigne, D. Barceló, S. Duchesne, J.P. Villeneuve, A.N. Rousseau, S. Tremblay and R.Tauler A6103
    10:30 - 10:50 'A data mining approach to discover weather patterns contributing to PM10 exceedances' Sfetsos A. and Vlachogiannis D. A6103
    11:20 - 11:40 'Virtual Sources for Spatio-temporal Monitoring Data Analysis' A. Nuzhny, E. Saveleva, S. Kazakov and S. Utkin A6103
    11:40 - 12:00 'Applying Data Mining Methods for Forest Planning Data Validation' A.Mäkinen, A.Kangas and T.Tokola A6103
    12:00 - 12:20 'Entropy-based fuzzy set optimisation for reducing ecological model complexity' A.M. Mouton, B. De Baets, A. Peter, G. Holzer, R. Müller and P.L.M. Goethals A6103
    12:20 - 12:40 'Identifying Biological Echoes in Radar Scans Using Machine Learning' R. Mead, J. Paxton and R.S. Sojda A6103
    12:40 - 13:00 'Statistical analysis of spatial plant patterns under the effect of forest use' I. López, T. Standovár, J. Garay , Z. Varga and M. Gámez A6103
    15:00 - 15:20 'Multivariate Spatio-Temporal Clustering (MSTC) as a Data Mining Tool for Environmental Applications' F.M. Hoffman, W.W. Hargrove, R.T. Mills, S. Mahajan, D.J. Erickson and R.J. Oglesby A6103
    15:20 - 15:40 'A Particle Swarm Optimization derivative applied to cluster analysis' J.L. Díaz, M. Herrera, J. Izquierdo, I. Montalvo, R. Pérez A6103
    15:40 - 16:00 'Automatic generation of conceptual descriptions of classifications in Environmental Domains' A. Perez-Bonilla, K. Gibert and D. Vrecko A6103
    16:00 - 16:20 'A neural network approach for selecting the most relevant variables for foaming in anaerobic digestion' J. Dalmau, J. Comas, I. Rodríguez-Roda, E. Latrille and J.-P. Steyer A6103
    16:40 - 17:00 'Trajectories’ Mining Between Subprocesses in a Wastewater Treatment Plant' K. Gibert, G. Rodríguez Silva and I. Rodríguez Roda A6103
    17:00 - 17:20 'Identifying State Variables in Multivariate Hydrological Time Series Using Time Series Knowledge Mining' O. Gronz, M. Casper, P. Gemmar A6103
    17:20 - 17:40 'Prediction of Significant Wave Height Based on Regression Trees' A. Etemad-Shahidi and J.Mahjoobi A6103