Knowledge-based prediction of pore diameter of nanoporous anodic aluminum oxide
作者： Mahdi Mohajeri , Hamed Akbarpour
DOI: 10.1016/J.JELECHEM.2013.07.026
关键词:
摘要: Using nanostructured materials, especially nanoporous aluminum oxide, becomes more popular in recent years. The main purpose of this paper is developing an artificial neural network (ANN) model and conducting experiment to predict the pore diameter oxide membrane. For reason, a total 32 experimental data are collected used develop proposed model. process parameters such as electrolyte concentration, temperature anodization potential considered input, while accounted for output. A comparison ANN, study two previous empirical formulas indicates that ANN has good predictive capability diameter. It can also forecast result with acceptable error. results reveal both too conservative.
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