ARTIFICIAL-NEURAL-NETWORK PREDICTION OF HEXAGONAL LATTICE PARAMETERS FOR NON-STOICHIOMETRIC APATITES


Kockan U., Ozturk F., EVİS Z.

MATERIALI IN TEHNOLOGIJE, vol.48, no.1, pp.73-79, 2014 (Journal Indexed in SCI) identifier

  • Publication Type: Article / Article
  • Volume: 48 Issue: 1
  • Publication Date: 2014
  • Title of Journal : MATERIALI IN TEHNOLOGIJE
  • Page Numbers: pp.73-79

Abstract

In this study, hexagonal lattice parameters (a and c) and unit-cell volumes of non-stoichiometric apatites of M-10(TO4)(6)X-2 are predicted from their ionic radii with artificial neural networks. A multilayer-perceptron network is used for training. The results indicate that the Bayesian regularization method with four neurons in the hidden layer with a tansig activation function and one neuron in the output layer with a purelin function gives the best results. It is found that the errors for the predicted data of the lattice parameters of a and c are less than 1 % and 2 %, respectively. On the other hand, about 3 % errors were encountered for both lattice parameters of the non-stoichiometric apatites with exact formulas in the presence of the T-site ions that are not used for training the artificial neural network.