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Support Vector Machine (SVM) is a useful technique for data classification with successful applications in different fields of bioinformatics, image segmentation, data mining, etc. A key problem of these methods is how to choose an optimal kernel and how to optimize its parameters in the learning process of SVM. The objective of this study is to propose a Genetic Algorithm approach for parameter optimization...
Thin-film transistor liquid-crystal display (TFT-LCD) manufacturing in Taiwan is booming; and the revenues from the TFT-LCD industry have grown significantly in recent years. One of the main problems in the TFT-LCD manufacturing process is to diagnose faulty products. This study employed support vector machines (SVM) with principal components analysis (PCA) to diagnose root causes in sputtering operations...
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