Naturally Modeling Electric Circuit Data Domain With Network Representation Scheme In AI

Ying-Kuei Yang

doi:10.1117/12.947025

29 March 1988 Naturally Modeling Electric Circuit Data Domain With Network Representation Scheme In AI

Ying-Kuei Yang

Proceedings Volume 0937, Applications of Artificial Intelligence VI; (1988) https://doi.org/10.1117/12.947025
Event: 1988 Technical Symposium on Optics, Electro-Optics, and Sensors, 1988, Orlando, FL, United States

Abstract

Many databases have been developed for electric circuit, designs based on the record-oriented conventional data, Models or their extensions. But these conventional data models and their extensions have been criticized as not, powerful enough to represent circuit information. In order to powerfully model circuit, data domain, we propose the use of semantic network technology developed in artificial intelligence (Al) as a data model to represent, circuit information. The result indicates that, the semantic network not only can model a circuit data domain but also mirrors the domain's origina1 structure which is the form most familiar to human beings. This is done rather than using acomplicated conversion algorithm to force translation of the primitives of the data domain into artificially specified constructs, as the conventional models do. This one- to-one correspondence between the data in the datalbase and the original data, makes it faster to incorporate data in the database and easier for database designers to set up and users to use a database system.

Citation Download Citation

Ying-Kuei Yang "Naturally Modeling Electric Circuit Data Domain With Network Representation Scheme In AI", Proc. SPIE 0937, Applications of Artificial Intelligence VI, (29 March 1988); https://doi.org/10.1117/12.947025

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