Using support vector regression for the prediction of the band gap and melting point of binary and ternary compound semiconductors

In this work, atomic parameters support vector regression (APSVR) was proposed to predict the band gap and melting point of III-V, II-VI binary and I-III-VI2, II-IV-V-2 ternary compound semiconductors. The predicted results of APSVR were in good agreement with the experimental ones. The prediction accuracies of different models were discussed on the basis of their mean error functions (MEF) in the leave-one-out cross-validation. It was found that the performance of APSVR model outperformed those of back propagation-artificial neural network (BP-ANN), multiple linear regression (MLR) and partial least squares regression (PLSR) methods. (c) 2005 Elsevier SAS. All rights reserved.