从计量结果来看，我们可以得出以下结论：

First of all, can be seen from Table 2: (1) Because the F-test P value of 0, the overall model is statistically significant, the model is better; (2) R2 values ​​up to 99.79%, the modified model is R2 99.75%, excellent fit and high, a high degree of fit model and the actual value established herein, preferably model; (3) Root Mse (residual standard deviation) is 0.03776, the smaller the value, the smaller the residual fluctuations the model more stable, better return.

First of all, we can see from Table 2: (1) Because the P value of F test is 0, the model population is statistically significant, the model is better; (2) R2 value is as high as 99.79%, the r2 value of the modified model is 99.75%, the fit is high, the model and actual value sits in this paper is very high, the model is better; Mse (residual standard deviation) is 0.03776, the value is small, the residual fluctuation is small, the model is more stable, the effect of regression is better.

First of all, it can be seen from table 2 that: (1) as the p value of F test is 0, the model is statistically significant and the model is good; (2) the R2 value is as high as 99.79%, the R2 value of the modified model is 99.75%, and the goodness of fit is high. The goodness of fit between the model established in this paper and the actual value is very high and the model is good; (3) the root MSE (standard deviation of residual) is 0.03776, the value is small, and the residual fluctuation is small. The model is stable and the effect of regression is good.<br>