Material removal rate prediction in chemical mechanical planarization with conditional probabilistic autoencoder and stacking ensemble learning
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DOI: 10.1007/s10845-022-02040-w
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References listed on IDEAS
- Ki Bum Lee & Chang Ouk Kim, 2020. "Recurrent feature-incorporated convolutional neural network for virtual metrology of the chemical mechanical planarization process," Journal of Intelligent Manufacturing, Springer, vol. 31(1), pages 73-86, January.
- Dazhong Wu & Yupeng Wei & Janis Terpenny, 2019. "Predictive modelling of surface roughness in fused deposition modelling using data fusion," International Journal of Production Research, Taylor & Francis Journals, vol. 57(12), pages 3992-4006, June.
- Edoardo M Airoldi, 2007. "Getting Started in Probabilistic Graphical Models," PLOS Computational Biology, Public Library of Science, vol. 3(12), pages 1-5, December.
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Keywords
Chemical mechanical planarization; Deep learning; Graphical model; Material removal rate prediction;All these keywords.
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