Hybrid Model for Intent Estimation

نویسندگان

  • Kangjin David Lee
  • James Llinas
چکیده

Real-time data acquired under combat conditions will have different types of imperfection; two representative classes of imperfection are vagueness and ambiguity in the data. A motivational example is created in this paper to explore the prototyping of a hybrid processing model that can formally process both vague (fuzzy) and ambiguous (probabilistic) data types. The issue is to integrate the heterogeneous models, which have different domains, probability and possibility. This research provides a hybrid model by exploring and adopting a transformation method between probability and possibility.

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تاریخ انتشار 2003