The presentation will provide the methodological background of Data Mining, including the Rough Sets Theory and its application in transportation. The historical background and the current status of the field will be characterized. Basic notions of the data mining methodology will be given. The classification of data mining methods will be presented and selected tools and algorithms will be discussed. The benefits of Rough Sets will be discussed and current developments in Rough Sets Theory will be presented. Different categories of transportation decision problems that can be handled by Rough Sets will be characterized. 2-3 case studies will be presented to demonstrate practical applicability of Data Mining (Rough Sets) in transportation, including:
- Technical Diagnostics of Vehicles; the analysis of information capacity of certain attributes; evaluation of the technical condition of trams and buses;
- Evaluation of the Quality of Transportation Systems; definition of the most suitable evaluation criteria.