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Book/Book Chapter 
Optimization of Process Parameters Based on ANN When Synthesizing Nano-size Hydroxyapatite in Aqueous Solution 
Niu, Z; Song, Kai; Li, ZhiY; Sima, ZWen 
Modelling and Simulation-World Academic Union 
The process parameters that influence the performance of synthesized nano-size hydroxyapatite powder such as purity, granularity, and crystallinity include the mass ratio between Ca(NO(3))(2)center dot 4H(2)O and (NH(4))(2)HPO(4), the PH value of reaction liquid, the temperature of sintering and the time of heat preservation. Back-propagation artificial neural network model was established to predict the performance of synsized hydroxyapatite and optimize the processing parameters. Orthogonal experiments with different process parameters are designed; experiments were carried out with every process parameter take 4 different values. The ANN model was trained using above experimental data. The optimization processing parameters to synsize nano-size hydroxyapatite were got. 
hydroxyapatite; nano-size; process parameter; optimization; artificial neural network