This study
presents the effort in applying neural network-based system
identification techniques by using Back-propagation algorithm to
predict some physical mechanical properties of functionally
graded and composite samples from Ti/HAP, these samples were
fabricated by powder metallurgy method at various volume
fraction of hydroxyapatite and at n equal (0.8, 1, and 1.2).
Because of important of advanced materials such as FGMs as
alternative industrial material, it is necessary to measure the
physical properties of these materials such as porosity,
density, hardness, compression …etc. Therefore the ANN will be
used to estimate these properties and give a good performance to
the network. |