@inproceedings{bcba1a1b7a3e42c4a150a90436b2ca40,
title = "PCA-based neural network modeling using the photoluminescence data for growth rate of ZnO thin films fabricated by pulsed laser deposition",
abstract = "The process modeling for the growth rate of pulsed laser deposition (PLD)-grown ZnO thin films was investigated using neural networks (NNets) based on the back-propagation (BP) algorithm and PCA-based NNets using photoluminescence (PL) data. D-optimal experimental design was performed and the growth rate was characterized by NNets. PCA-based NNets were then carried out in order to build the model by PL data. The statistical analysis for those results was then used to verify the fitness of the nonlinear process model. Based on the results, this modeling methodology can explain the characteristics of the thin film growth mechanism varying with process conditions and the model can be analyzed and predicted by the multivariate data.",
author = "Lee, {Jung Hwan} and Ko, {Young Don} and Jeong, {Min Chang} and Myoung, {Jae Min} and Ilgu Yun",
year = "2006",
doi = "10.1007/11760191_160",
language = "English",
isbn = "3540344829",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "1099--1104",
booktitle = "Advances in Neural Networks - ISNN 2006",
address = "Germany",
note = "3rd International Symposium on Neural Networks, ISNN 2006 - Advances in Neural Networks ; Conference date: 28-05-2006 Through 01-06-2006",
}