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Methodology of diagnostic knowledge acquisition from databases of examples

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

Abstract

The diagnostics of a critical machinery is nowadays aided by expert systems. Their knowledge bases contain knowledge on diagnostic relationships between a technical state of a given machine, its operating conditions and observable symptoms of this state. This knowledge may be acquired either from human experts or from databases containing examples. The paper focuses on problems of knowledge acquisition from examples. It concerns the whole range of problems starting from preparation of examples up to the verification and validation of the knowledge base at the end of the proceeding. To acquire diagnostic knowledge from a set of examples we apply both machine learning and knowledge discovery methods. An example of the application of described methods for the acquisition of knowledge suitable for diagnosing complex technical states of rotating machinery is also given.

Original languageEnglish
Title of host publicationIntelligent Information Systems -Proceedings of the IIS'2000 Symposium
Pages175-184
Number of pages10
EditionAISC
DOIs
Publication statusPublished - 2000
Event9th Intelligent Information Systems Symposium, IIS'2000 - Bystra, Poland
Duration: 12 Jun 200016 Jun 2000

Publication series

NameAdvances in Soft Computing
NumberAISC
Volume4
ISSN (Print)1615-3871
ISSN (Electronic)1860-0794

Conference

Conference9th Intelligent Information Systems Symposium, IIS'2000
Country/TerritoryPoland
CityBystra
Period12/06/0016/06/00

Keywords

  • complex technical states
  • knowledge acquisition
  • knowledge discovery
  • learning from examples
  • machinery diagnostics

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Computational Mechanics
  • Computer Science Applications

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