Data mining, knowledge discovery and data-driven modelling

The project was aimed at exploring the possibilities of a new paradigm in modelling - data-driven modelling, often referred as "data mining". Several application areas were considered: sedimentation problems in the Port of Rotterdam, automatic soil classification on the basis of cone penetration tests, prediction of water levels in the ocean, and others. The methods applied included: artificial neural networks, fuzzy systems, M5 model trees, chaos theory. The knowledge was disseminated using the following means: several publications at the conferences and peer-reviewed journals, Symposium for 80 Dutch participants from various civil engineering organisations (April 2002), Web-based platform with the main project results, software and knowledge base of best practices and publications. The developed research methodologies were practically used in the Delft Cluster research Themes and by external partners. Two PhD researches are underway and 4 MSc projects were successfully completed. A comprehensive Knowledge Platform ( http://datamining.ihe.nl) was built; it includes the educational components, links to the news and events in the area of data-driven modelling, knowledge base with the publications, software and best practices, and software with the examples of real case studies. The achieved results make possible to conclude that the data-driven methods can be effectively used in a wide range of civil engineering problems, complementing and sometimes replacing more traditional simulation models