ITR: A Real Time Mining of Integrated Weather Data

University Of Oklahoma Norman Campus, Norman OK

Investigators

Abstract

EIA-0205628 Theodore B. Trafalis University of Oklahoma ITR: A Real Time Mining of Integrated Weather Data The mission is to build systems and develop theory for extracting information and identifying patterns that are useful for making decision in real-time. Funding is being requested to build pattern recognition techniques that will exploit multisensor data in an integrated manner to provide information such as the presence or absence of tornados, supercells and mesocyclones; estimate precipitation; predict the occurrence of flash floods; assimilate and display large volumes of multisensor data and trigger the archive of selected data sets. These tasks will be accomplished by customizing and developing techniques for real-time data mining. The approaches used will include traditional data reduction methods such as PCA and clustering; Procrustes analysis; Kalman filters and non-linear time series analysis with regime switching; and, decomposition and robust optimization methods for training support vector machines.