Journal
Article title
Authors
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Abstracts
A model based on artificial neural network was designed for the simulation and estimation of glass forming ability parameters and saturation magnetization and coercivity of bulk glassy alloys. Its performance is evaluated by the influences of different kinds of alloys and elements on the glass forming ability and magnetic properties. The values of glass forming ability parameters and saturation magnetization and coercivity values estimated by artificial neural network agree well with the experimental values, indicating that the model is reliable and adequate.
Discipline
- 84.35.+i: Neural networks(for optical neural networks, see 42.79.Ta; see also 07.05.Mh Neural networks, fuzzy logic, artificial intelligence in computers in experimental physics; 87.18.Sn in biological complexity)
- 75.50.Vv: High coercivity materials
- 75.50.Kj: Amorphous and quasicrystalline magnetic materials
- 64.70.pe: Metallic glasses
Journal
Year
Volume
Issue
Pages
827-828
Physical description
Dates
published
2010-11
Contributors
author
- Physics Department, Faculty of Arts and Sciences, Uludag University, Gorukle Campus 16059, Bursa, Turkey
author
- Physics Department, Faculty of Arts and Sciences, Uludag University, Gorukle Campus 16059, Bursa, Turkey
author
- Physics Department, Faculty of Arts and Sciences, Uludag University, Gorukle Campus 16059, Bursa, Turkey
References
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Document Type
Publication order reference
Identifiers
YADDA identifier
bwmeta1.element.bwnjournal-article-appv118n5047kz