반도체 제조 가상계측 공정변수를 이용한 웨이퍼 수율 예측 / A Prediction of Wafer Yield Using Product Fabrication Virtual Metrology Process Parameters in Semiconductor Manufacturing
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[1] D. Hosmer,et al. Applied Logistic Regression , 1991 .
[2] Sungzoon Cho,et al. Estimating the Reliability of Virtual Metrology Predictions in Semiconductor Manufacturing : A Novelty Detection-based Approach , 2012 .
[3] Shane A. Lynn,et al. Global and Local Virtual Metrology Models for a Plasma Etch Process , 2012, IEEE Transactions on Semiconductor Manufacturing.
[4] Ron Kohavi,et al. A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection , 1995, IJCAI.
[5] J. Ross Quinlan,et al. Induction of Decision Trees , 1986, Machine Learning.
[6] Han, Chang Hee,et al. Application of Data mining for improving and predicting yield in wafer fabrication system , 2003 .
[7] Hyoungjoo Lee,et al. A virtual metrology system for semiconductor manufacturing , 2009, Expert Syst. Appl..
[8] Sungzoon Cho,et al. EUS SVMs: Ensemble of Under-Sampled SVMs for Data Imbalance Problems , 2006, ICONIP.
[9] James Moyne,et al. Virtual metrology and feedback control for semiconductor manufacturing processes using recursive partial least squares , 2008 .
[10] Douglas C. Montgomery,et al. A review of yield modelling techniques for semiconductor manufacturing , 2006 .
[11] Reha Uzsoy,et al. A REVIEW OF PRODUCTION PLANNING AND SCHEDULING MODELS IN THE SEMICONDUCTOR INDUSTRY PART I: SYSTEM CHARACTERISTICS, PERFORMANCE EVALUATION AND PRODUCTION PLANNING , 1992 .
[12] Stan Matwin,et al. Machine Learning for the Detection of Oil Spills in Satellite Radar Images , 1998, Machine Learning.
[13] B. T. Murphy,et al. Cost-size optima of monolithic integrated circuits , 1964 .
[14] Chi-Hyuck Jun,et al. The Comparison and Use of Yield Models in Semiconductor Manufacturing , 1997 .
[15] Cheng-Lung Huang,et al. Data Mining using Genetic Programming for Construction of a Semiconductor Manufacturing Yield Rate Prediction System , 2006, J. Intell. Manuf..
[16] Haw Ching Yang,et al. Multivariate simulation assessment for virtual metrology , 2006, Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006..
[17] Chung Kwan Shin,et al. A machine learning approach to yield management in semiconductor manufacturing , 2000 .
[18] A. Ferreira,et al. Virtual Metrology models for predicting physical measurement in semiconductor manufacturing , 2009, 2009 IEEE/SEMI Advanced Semiconductor Manufacturing Conference.
[19] VARUN CHANDOLA,et al. Anomaly detection: A survey , 2009, CSUR.
[20] Leo Breiman,et al. Random Forests , 2001, Machine Learning.
[21] Yuan Kang,et al. Virtual Metrology Technique for Semiconductor Manufacturing , 2006, The 2006 IEEE International Joint Conference on Neural Network Proceedings.
[22] Nitesh V. Chawla,et al. SMOTE: Synthetic Minority Over-sampling Technique , 2002, J. Artif. Intell. Res..
[23] Andy Liaw,et al. Classification and Regression by randomForest , 2007 .
[24] Hyoungjoo Lee,et al. Virtual metrology for run-to-run control in semiconductor manufacturing , 2011, Expert Syst. Appl..
[25] Hyo-Heon Ko,et al. A semiconductor yields prediction using stepwise support vector machine , 2009, 2009 IEEE International Symposium on Assembly and Manufacturing.
[26] Costas J. Spanos,et al. Semiconductor yield improvement: results and best practices , 1995 .
[27] F ROSENBLATT,et al. The perceptron: a probabilistic model for information storage and organization in the brain. , 1958, Psychological review.
[28] 전치혁,et al. 반도체 제조업에서 사용되는 수율 모델의 비교 및 이용 , 1997 .
[29] C.H. Yu,et al. Virtual metrology: a solution for wafer to wafer advanced process control , 2005, ISSM 2005, IEEE International Symposium on Semiconductor Manufacturing, 2005..
[30] Wen-Chih Wang,et al. Data mining for yield enhancement in semiconductor manufacturing and an empirical study , 2007, Expert Syst. Appl..