Proceedings of the KIEE Conference (대한전기학회:학술대회논문집)
- 2006.10c
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- Pages.211-213
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- 2006
Modeling of Plasma Process Using Support Vector Machine
Support Vector Machine을 이용한 플라즈마 공정 모델링
Abstract
In this study, plasma etching process was modeled by using support vector machine (SVM). The data used in modeling were collected from the etching of silica thin films in inductively coupled plasma. For training and testing neural network, 9 and 6 experiments were used respectively. The performance of SVM was evaluated as a function of kernel type and function type. For the kernel type, Epsilon-SVR and Nu-SVR were included. For the function type, linear, polynomial, and radial basis function (RBF) were included. The performance of SVM was optimized first in terms of kernel type, then as a function of function type. Five film characteristics were modeled by using SVM and the optimized models were compared to statistical regression models. The comparison revealed that statistical regression models yielded better predictions than SVM.