Performance of neural networks in materials science
- Title
- Performance of neural networks in materials science
- Date Issued
- 2009-04
- Publisher
- MANEY PUBLISHING
- Abstract
- Neural networks are now a prominent feature of materials science with rapid progress in all sectors of the subject. It is premature, however, to claim that the method is established. There are genuine difficulties caused by the often incomplete exploration and publication of models. The assessment presented here is an attempt to compile a loose set of guidelines for maximising the impact of any models that are created, in order to encourage thoroughness in publication to a point where the work can be independently verified.
- Keywords
- Neural network; Materials science; Materials modelling; Uncertainties; Errors; AUSTENITIC STAINLESS-STEEL; STRAIN-INDUCED TRANSFORMATION; PRINCIPAL COMPONENT ANALYSIS; TRIP-AIDED STEELS; MECHANICAL-PROPERTIES; MAGNETIC-PROPERTIES; RETAINED AUSTENITE; IMPACT TOUGHNESS; TENSILE-STRENGTH; TITANIUM-ALLOYS
- URI
- https://oasis.postech.ac.kr/handle/2014.oak/29015
- DOI
- 10.1179/174328408X31
- ISSN
- 0267-0836
- Article Type
- Article
- Files in This Item:
- There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.