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A Novel Chamber Scheduling Method in Etching Tools Using Adaptive Neural Networks.
- Source :
- Advances in Neural Networks - ISNN 2005; 2005, p908-913, 6p
- Publication Year :
- 2005
-
Abstract
- Chamber scheduling in etching tools is an important but difficult task in integrated circuit manufacturing. In order to effectively solve such combinatorial optimization problems in etching tools, this paper presents a novel chamber scheduling approach on the base of Adaptive Artificial Neural Networks (ANNs). Feed forward, multi-layered neural network meta-models were trained through the back-error-propagation (BEP) learning algorithm to provide a versatile job-shop scheduling analysis framework. At the same time, an adaptive selection mechanism has been extended into ANN. By testing the practical data set, the method is able to provide near-optimal solutions for practical chamber scheduling problems, and the results are superior to those generated by what have been reported in the neural network scheduling literature. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISBNs :
- 9783540259145
- Database :
- Complementary Index
- Journal :
- Advances in Neural Networks - ISNN 2005
- Publication Type :
- Book
- Accession number :
- 32883970
- Full Text :
- https://doi.org/10.1007/11427469_144