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Integrating symbolic and numerical features for fault prediction and diagnosis by an expert system
Author(s) -
Angeli Chr
Publication year - 1999
Publication title -
expert systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.365
H-Index - 38
eISSN - 1468-0394
pISSN - 0266-4720
DOI - 10.1111/1468-0394.00114
Subject(s) - computer science , expert system , knowledge base , task (project management) , machine learning , data mining , fault (geology) , knowledge based systems , artificial intelligence , software engineering , data science , systems engineering , seismology , engineering , geology
This paper addresses the topic of a predictive task after integration of symbolic and numerical features by a hybrid diagnostic expert system. The online interaction of information and knowledge from various sources is achieved after successful combination of different development environments, tools and programs. The system infers using cooperatively dynamic modelling information, online sensor information, and stored knowledge in the knowledge base.