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Minimisation methods for training feedforward neural networks

โœ Scribed by P. Patrick van der Smagt


Publisher
Elsevier Science
Year
1994
Tongue
English
Weight
872 KB
Volume
7
Category
Article
ISSN
0893-6080

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โœ YIMIN FAN; C.JAMES LI ๐Ÿ“‚ Article ๐Ÿ“… 2002 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 272 KB

This paper describes a method of extracting diagnostic rules from trained diagnostic feedforward neural nets that are constructed to recognise di!erent mechanical faults using automated weight and structure learning algorithms. The rule extracting method is based on an interpretation that considers