Intelligent simulation tools for mining large scientific data sets |
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Authors: | Feng Zhao Chris Bailey-Kellogg Xingang Huang Iván Ordóñez |
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Affiliation: | (1) Xerox Palo Alto Research Center, 3333 Coyote Hill Road, 94304 Palo Alto, CA;(2) Dartmouth College, 6211 Sudikoff Laboratory, 03755 Hanover, NH;(3) The Ohio State University, 2015 Neil Avenue, 43210 Columbus, OH |
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Abstract: | This paper describes problems, challenges, and opportunities forintelligent simulation of physical systems. Prototype intelligent simulation tools have been constructed for interpreting massive data sets from physical fields and for designing engineering systems. We identify the characteristics of intelligent simulation and describe several concrete application examples. These applications, which include weather data interpretation, distributed control optimization, and spatio-temporal diffusion-reaction pattern analysis, demonstrate that intelligent simulation tools are indispensable for the rapid prototyping of application programs in many challenging scientific and engineering domains. |
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Keywords: | Intelligent Simulation Scientific Data Mining Qualitative Reasoning Reasoning about Physical Systems Programming Environments |
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