Adaptive Network-Based Fuzzy Inference Model of Plasma Enhanced Chemical Vapor Deposition Process
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Publisher
Springer Berlin Heidelberg
Link
http://link.springer.com/content/pdf/10.1007/978-3-540-72383-7_71
Reference11 articles.
1. Kim, B., Kwon, K.H., Kwon, S.K., Park, J.M., Yoo, S.W., Park, K.S., You, I.K., Kim, B.W.: Modeling Etch and Uniformity of Oxide via Etching in a CHF3/CF4 Plasma Using Neural Network. Thin Solid Films 426, 8–15 (2003)
2. Kim, B., Kim, S.: GA-optimized Backpropagation Neural Network with Multi-parameterized Gradients and Applications to Predicting Plasma Etch Data. Chemometr. Intell. Lab. Syst. 79, 123–128 (2005)
3. Kim, B., Kim, S.: Plasma Diagnosis by Recognizing in-situ Data Using a Modular Backpropagation Network. Chemomemetr. Intell. Lab. Syst. 65(2), 231–240 (2003)
4. Kim, B., Kim, S., Lee, B.T.: Modeling SiC Surface Roughness Using Neural Network and Atomic Force Microscopy. J. Vac. Sci. Technolo. B 22(5), 2467–2472 (2004)
5. Kim, B., Kim, K.: Prediction of Profile Surface Roughness in CHF3/CF4 Plasma Using Neural Network. Applied Surface Science 222(1-4), 17–22 (2004)
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