Application of Improved Back-propagation Neural Network to the Technologic Processing of Korshunskite Whiskers

The korshunskite samples were prepared in precipitation by the one-step reaction method at atmospheric pressure. The three-layer structure back-propagation network model based on the non-linear relationship between the amount of the korshunskite whiskers and the technological factors, such as the adding amount of raw materials of NaOH, MgCl2, MgO, and reaction temperature, is established. And the results show that the improved back propagation neural networks model is very efficient for predication of the korshunskite whiskers preparation.