| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 1562664 | Computational Materials Science | 2011 | 10 Pages |
Abstract
⺠Different Computational Intelligence approaches are employed for predicting Lattice Constants of complex cubic perovskites. ⺠A total of 197 perovskites compounds are collected from the recent literature of materials science. ⺠High prediction performance is achieved using Support Vector Regression and Random Forest. ⺠For some of the compounds, the large prediction error is correlated with the structure deviation of these compounds from ideal cubic structure.
Keywords
Related Topics
Physical Sciences and Engineering
Engineering
Computational Mechanics
Authors
Abdul Majid, Asifullah Khan, Tae-Sun Choi,