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Home >> Research >> Thrust Areas >> Data Mining

Thrust Area III: Information Technology Applications

INVESTIGATORS: NCA&T: Homaifar, Esterline, Li, Nzewi, Hagevik, Samanlioglu; NCSU: Kang; CUNY: Grossberg; FU: Caulfield, Qian; UM: Kumar, UA: Heavner

Summary: Analyzing, correlating, and interpreting large volumes of data from extensive networks of heterogeneous sensors present a challenge for state-of-the-art data fusion.  Also, traditional data-mining techniques are challenged by the complex, dynamic relationships to be discovered in large volumes of climate data (including image data).  Adequate solutions for the fusion, mining, and analysis of climate data likely will involve non-traditional architectures, such as grids, which make vast data and computational resources transparently available to users, and multiagent systems, which use flexible problem-solving protocols to allow persistent computational entities to collaborate.  Accordingly, the tasks covered by this group include (1) combining physical models and statistical learning for data fusion, (2) applying fuzzy integrals and measures as well as decision optimization for data fusion, (3) mining earth observing system satellite data, (4) image-database mining, (5) modeling and visualization through geospatial data models, (6) multiagent systems for data fusion, and (7) grid computing for mining spatio-temporal patterns.

View the latest project information: Thrust Area III- Research Area III-C

This website was prepared by North Carolina Agricultural & Technical State University under award number NA06OAR4810187 from the National Oceanic and Atmospheric Administration, U.S. Department of Commerce.  The statements, findings, conclusions, and recommendations are those of the author and do not necessarily reflect the views of the National Oceanic and Atmospheric Administration or the U.S. Department of Commerce.