TY - JOUR
T1 - A comparison of the artificial neural network model and the theoretical model used for expressing the kinetics of electrophoretic deposition of YSZ on LSM
AU - Ciou, Sian Jie
AU - Fung, Kuan-Zong
AU - Chiang, Kai-Wei
PY - 2008/1/3
Y1 - 2008/1/3
N2 - In the present study, an artificial neural network (ANN) model and a theoretical model are established to predict the kinetic behavior of electrophoretic deposition (EPD). Both the theoretical model and the ANN model describe the kinetic behavior of EPD at a low-applied voltage (below 15 V) well. However, the theoretical model failed to predict the behavior at the higher applied voltages of 40 and 50 V. In contrast, the proposed ANN model not only showed enhanced numerical accuracy, but was also generic to other operational conditions as well. Compared to the theoretical model, the ANN model shows outstanding capability of predicting actual kinetic behavior.
AB - In the present study, an artificial neural network (ANN) model and a theoretical model are established to predict the kinetic behavior of electrophoretic deposition (EPD). Both the theoretical model and the ANN model describe the kinetic behavior of EPD at a low-applied voltage (below 15 V) well. However, the theoretical model failed to predict the behavior at the higher applied voltages of 40 and 50 V. In contrast, the proposed ANN model not only showed enhanced numerical accuracy, but was also generic to other operational conditions as well. Compared to the theoretical model, the ANN model shows outstanding capability of predicting actual kinetic behavior.
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U2 - 10.1016/j.jpowsour.2007.09.024
DO - 10.1016/j.jpowsour.2007.09.024
M3 - Article
AN - SCOPUS:36348996057
VL - 175
SP - 338
EP - 344
JO - Journal of Power Sources
JF - Journal of Power Sources
SN - 0378-7753
IS - 1
ER -