Title of article :
Lattice constant prediction of orthorhombic ABO3 perovskites using support vector machines
Author/Authors :
Javed، نويسنده , , Syed Gibran and Khan، نويسنده , , Asifullah and Majid، نويسنده , , Zaiton Abdul and Mirza، نويسنده , , Anwar M. and Bashir، نويسنده , , J.، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2007
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 :
Machine Learning , Artificial neural networks , Percentage absolute difference , perovskites , lattice constant , Atomic parameters , Support vector machine
Journal title :
Computational Materials Science
Journal title :
Computational Materials Science