Prediction of the unit cell edge length of cubic A22+BB′O6 perovskites by multiple linear regression and artificial neural networks

Optimization of artificial neural networ

Optimization of artificial neural networks for prediction of the unit cell parameters in orthorhombic perovskites. Comparison with multiple linear regression

✍ Igor Kuzmanovski; Slobotka Aleksovska 📂 Article 📅 2003 🏛 Elsevier Science 🌐 English ⚖ 314 KB

The unit cell parameters (a, b, c) of orthorhombic perovskites (of A 2 + B 4 + O 3 and A 3 + B 3 + O 3 type) were predicted both using multiple linear regression analysis (MLR) and two types of artificial neural networks (ANN). In these analyses, 70 compounds of above perovskite type were included: