Knowledge Discovery Laboratory (KDL)

The Knowledge Discovery Laboratory (KDL) conducts research and education in data bases, data warehouse, OLAP, data mining, computational Intelligence (e.g. Artificial Neural Networks, Fuzzy Logic Systems, Genetic Algorithms), and other computational intelligence theories for applications in enterprises, such as business, industry, healthcare, and service organizations. Funding from government agencies and industrial corporations has led to the development of new solutions in areas such as engineering design (e.g., process analysis, design automation, autonomous decision making, and reengineering), manufacturing (e.g., system design, planning and scheduling, reconfigurable systems, e-business, and system maintenance and diagnosis), and medicine (e.g., disease diagnosis, generation of medical protocols, and discovery of medical knowledge).

The research activities of the Knowledge Discovery Laboratory are coordinated by Prof. Kesheng Wang, who is a Professor in the Department of Production and Quality Engineering at the Norwegian University of Science and Technology. Ongoing industrial and government-funded research projects are conducted by researchers by SINTEF, graduate and undergraduate students from the Department of Production and Quality Engineering.

The Knowledge Discovery Laboratory pursues a dynamic research program that reflects the progress of the industrial engineering profession, as well as the needs of the laboratory's industrial and healthcare partners. Current research focus on the four topics:

  1. Knowledge discovery and Data Mining in engineering, science and environment
  2. Applied Computational Intelligence theory and applications
  3. Enterprise Decision Making and Optimization.
  4. Knowledge Management and Business Intelligence
  5. Swarm Intelligence in manufacturing and business: The research activity is directed towards enabling robust, cost-efficient, self-organizing and self-repairing highly dynamic networks and tele-service providing systems. To develop technology for cost efficient provision of differentiated dependability. An important means to pursue this is PSO and ACO ("ant-like" mobile agent technology). Validate the quantitative properties of these solutions by modeling, analysis, simulation and measurements.
  6. New renewable energy – Generate power fro DiElectrical Active Polymer (DEAP)