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|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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