Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/13476
Title: Automated extraction of diagnostic knowledge
Authors: Zhai, Lianyin
Keywords: DRNTU::Engineering::Manufacturing::Production management
DRNTU::Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence
Issue Date: 1999
Abstract: With the advent in technology, manufacturing systems have become more complex. It may not be easy for an engineer to acquire sufficient knowledge in a short time in order to carry out manufacturing diagnosis efficiently. As a result, the ability to automatically extract diagnostic rules from the raw knowledge or data gleaned from a manufacturing system has become an important area in artificial intelligence research. In reality, the raw knowledge gleaned from a manufacturing system may contain uncertainty, that is, it may be imprecise or incomplete.
URI: http://hdl.handle.net/10356/13476
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:MAE Theses

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