Hybrid Intelligent Systems for Data-Driven Monitoring

Wednesday, December 4, 2002 - 11:00am - 11:50am
Keller 3-180
Arthur Kordon (Dow Chemical Company)
A novel approach for data-driven modeling based on integration of four key computational intelligence approaches (genetic programming, analytical neural networks, support vector machines, and particle swarm optimizers) is proposed. The integrated methodology amplifies the advantages of the individual techniques, significantly reduces the development time, and delivers robust empirical models with low maintenance cost. The advantages of the proposed methodology for data-driven monitoring and optimization will be illustrated with several successful applications in The Dow Chemical Company.