Learning design rules and concepts for examples--A case study to design an electric power substation design

Y. B. Mahdy*, E. K. Stanek, M. Abdel-Salam, M. Zaki

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Some principles of machine learning and some links with knowledge base system are described. A domain-independent inductive learning system (ILS) has been developed and implemented. ILS can be attached to any expert system, and will work as a knowledge acquisition module for the expert system. This gives the expert system the ability to update and expand its knowledge base according to the circumstances. ILS is a logic-based, data-driven learning system, focusing on the problem of learning structural descriptions. ILS is tailored to design electrical system components. In the present work, ILS is used for specifying the major components of an electrical substation. The learning system will learn design rules and concepts from positive and negative examples in the form of existing substations. This system will take examples and generate rules and concepts for specifying the major components of an electric substation.

Original languageEnglish
Title of host publication1991 IEEE Industry Application Society Annual Meeting
PublisherPubl by IEEE
Pages1206-1215
Number of pages10
ISBN (Print)0780304535
StatePublished - 1991

Publication series

Name1991 IEEE Industry Application Society Annual Meeting

ASJC Scopus subject areas

  • General Engineering

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