Lattice constant prediction of orthorhombic ABO3 perovskites using support vector machines

被引:55
作者
Gibran Javed, Syed
Khan, Asifullah [1 ]
Majid, Abdul
Mirza, Anwar M.
Bashir, J.
机构
[1] Pakistan Inst Engn & Appl Sci, Dept Informat & Comp Sci, Islamabad, Pakistan
[2] Inst Engn Sci & Technol, Fac Comp Sci & Engn, Swabi, Pakistan
[3] Natl Univ Comp & Emerging Sci, Dept Comp Sci, Islamabad, Pakistan
[4] PINSTECH, Phys Res Dev, Islamabad, Pakistan
关键词
perovskites; lattice constant; atomic parameters; support vector machine; percentage absolute difference; machine learning; artificial neural networks;
D O I
10.1016/j.commatsci.2006.08.015
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
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 ABO(3) perovskites demonstrate that our proposed prediction model is more efficient, robust and fast than those based on artificial neural networks. (C) 2006 Elsevier B.V. All rights reserved.
引用
收藏
页码:627 / 634
页数:8
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