Modeling and optimization of the growth rate for ZnO thin films using neural networks and genetic algorithms

@article{Ko2009ModelingAO,
  title={Modeling and optimization of the growth rate for ZnO thin films using neural networks and genetic algorithms},
  author={Young-Don Ko and Pyung Moon and Chang Eun Kim and Moon-Ho Ham and Jaemin Myoung and Ilgu Yun},
  journal={Expert Syst. Appl.},
  year={2009},
  volume={36},
  pages={4061-4066}
}
The process modeling for the growth rate in pulsed laser deposition (PLD)-grown ZnO thin films was investigated using neural networks (NNets) based on the back-propagation (BP) algorithm and the process recipes was optimized via genetic algorithms (GAs). Two input factors were examined with respect to the growth rate as the response factor. D-optimal experimental design technique was performed and the growth rate was characterized by NNets based on the BP algorithm. GAs was then used to search… CONTINUE READING

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