Parameter optimization of double-blade normal milk processing and mixing performance based on RSM and BP-GA.

The variance analysis results of response surface model in Table 3 show that, the regression model p < .0001, indicating that the model was extremely significant; the Lack of fit p (.0964) was higher than .05, which was not significant, indicating that within the test range, the predicted values of the regression model fitted the actual values, determination coefficient of the variable coefficient R 2 was 0.9772, showing that the regression model could explain the 97.7% variability of test data and the predicted values were highly correlated with actual values, and this model can be used to analyze and predict temperature stability. 3.2.

also in 7,787 other papers