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
โฆ LIBER โฆ
Rule extraction from trained neural networks using genetic algorithms
โ Scribed by A. Duygu Arbatli; H. Levent Akin
- Publisher
- Elsevier Science
- Year
- 1997
- Tongue
- English
- Weight
- 526 KB
- Volume
- 30
- Category
- Article
- ISSN
- 0362-546X
No coin nor oath required. For personal study only.
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