Discovery of Concurrent Data Models from Experimental Tables: A Rough Set Approach

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The main objective of machine discovery is the determination of relations between data and of data models. In the paper we describe a method for discovery of data models represented by concurrent systems from experimental tables. The basic step consists in a determination of rules which yield a decomposition of experimental data tables; the components are then used to define fragments of the global system corresponding to a table. The method has been applied for automatic data models discovery from experimental tables with Petri nets as models for concurrency.