Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1564393 | Computational Materials Science | 2007 | 8 Pages |
Abstract
In this paper, a novel lattice constant prediction model based on support vector machine is proposed. In this proposed technique, advanced data set generation technique is also used which is helpful to develop fairly generalized prediction models. This enables us to achieve improved prediction performance of lattice constant of structurally known perovskites. Experimental results obtained using orthorhombic ABO3 perovskites demonstrate that our proposed prediction model is more efficient, robust and fast than those based on artificial neural networks.
Keywords
Related Topics
Physical Sciences and Engineering
Engineering
Computational Mechanics
Authors
Syed Gibran Javed, Asifullah Khan, Abdul Majid, Anwar M. Mirza, J. Bashir,