Method for resolving the consistency problem between rule-based and quantitative models using fuzzy simulation

Gyooseok Kim; Paul A. Fishwick

doi:10.1117/12.276731

20 June 1997 Method for resolving the consistency problem between rule-based and quantitative models using fuzzy simulation

Gyooseok Kim, Paul A. Fishwick

Author Affiliations +

Proceedings Volume 3083, Enabling Technology for Simulation Science; (1997) https://doi.org/10.1117/12.276731
Event: AeroSense '97, 1997, Orlando, FL, United States

Abstract

Given a physical system, there are experts who have knowledge about how this system operates. In some cases, there exits quantitative knowledge in the form of deep models. One of the main issues dealing with these different types of knowledge is 'how does one address the difference between the two model types, each of which represents a different level of knowledge about the system?' We have devised a method that starts with (1) the expert's knowledge about the system, and (2) a quantitative model that can represent all or some of the behavior of the system. This method then adjusts the knowledge in either the rule-based system or the quantitative system to achieve some degree of consistency between the two representations. Through checking and resolving the inconsistencies, we provide a way to obtain better models in general about systems by exploiting knowledge at all levels, whether qualitative or quantitative.

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Gyooseok Kim and Paul A. Fishwick "Method for resolving the consistency problem between rule-based and quantitative models using fuzzy simulation", Proc. SPIE 3083, Enabling Technology for Simulation Science, (20 June 1997); https://doi.org/10.1117/12.276731

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