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Combining KPCA with LSSVM for the Mooney-Viscosity Forecasting
2008 Second International Conference on Genetic and Evolutionary Computing, 2008Least squares support vector machine (LSSVM) has been used in soft sensor modeling in recent years. In developing a successful model based on LSSVM, the first important step is feature extraction. Principal components analysis (PCA) is a usual method for linear feature extraction and kernel PCA (KPCA) is a nonlinear PCA developed by using the kernel ...
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