Quality evaluation based on multivariate statistical forecasting methods

In process industry, combination forecasting methods have been proposed to be applied to evaluate product quality. In this paper, multivariate statistical combination forecasting models based on individual forecasting methods which contain principal component regression method (PCR), partial least squares regression method (PLSR) and modified partial least squares regression method (MPLSR) are established to predict wine quality. After the comparison among these methods, the superior one will be obtained. This work can help human experts to evaluate the wine quality and make the result more accurate.

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