Using Data Mining Tools To Build Integrated Discrete-Event Simulations
Building a simulation from disparate software requires analysis to establish commonality of code. The ability of a data mining tool to extract repeating functional structures and data flows is the first essential step to reduce exploration, save development time, and re-use simulation software compo...
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Format: | Tagungsbericht |
Sprache: | eng |
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Zusammenfassung: | Building a simulation from disparate software requires analysis to establish commonality of code. The ability of a data mining tool to extract repeating functional structures and data flows is the first essential step to reduce exploration, save development time, and re-use simulation software components. Such a tool must not only drill down to the atomic data but also roll-up to "10,000 feet" to reveal the relationships and hierarchies that allow event based simulations to interact. Computer Sciences Corporation (CSC) is developing a system for analysis of discrete event data structures defined by a set of nodes and links between those nodes. The Model Integration Application (MIA) is an integrated suite of tools that perform data mining to generate a representation in IDEF0 format, which then provides a description of the basic simulation activities and Input/Output interfaces. MIA allows for connection of the simulations along established rules and protocols in accordance with the IDEF0 standard. |
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ISSN: | 0891-7736 1558-4305 |
DOI: | 10.1109/WSC.2007.4419902 |