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- Title
COMPARISON OF USAGE OF DIFFERENT NEURAL STRUCTURES TO PREDICT AAO LAYER THICKNESS.
- Authors
Vagaská, Alena; Gombár, Miroslav
- Abstract
The paper deals with the comparison of usage of three basic types of neural units in order to create the most suitable model predicting determining the final thickness of the alumina layer formed at surface with current density of 1 A∙dm−2. In addition, the reliability of obtained prediction models, depending on the amount of training data, has been monitored. With properly selected range of training data it is possible to create prediction models with reliability greater than 95 % with achieved toleration 2×10−6 mm.
- Subjects
ARTIFICIAL neural networks; ANODIC oxidation of metals; DATA analysis; PREDICTION models; COMPARATIVE studies
- Publication
Technical Gazette / Tehnički Vjesnik, 2017, Vol 24, Issue 2, p333
- ISSN
1330-3651
- Publication type
Article
- DOI
10.17559/TV-20140423164817