当取矩阵R的第i行，该行表示的是因素R_i与其他各因素的相关性系数，称

When taking the i-th row of the matrix R, this row represents the correlation coefficient between the factor R_i and other factors, which is called the correlation coefficient between the single factors. <br>The judgment matrix is ​​generally a pairwise comparison matrix [18]. Suppose n factors A_1, A_2,..., A_n, the importance of each factor is a non-zero value d_1, d_2,..., d_n, then the element value of the judgment matrix is ​​the ratio of the importance of each factor, as in formula (3) Shown.

When taking the ith row of matrix R, this row represents factor R_ The correlation coefficient between I and other factors is called the correlation coefficient between the single factor.<br>The judgment matrix is generally a pairwise comparison matrix [18]. Let n factors a_ 1,A_ 2,…,A_ n. The importance value of each factor is non-zero D_ 1,d_ 2,…,d_ n. Then the element value of the judgment matrix is the ratio of the importance value of each factor, as shown in equation (3).

When the I-th row of matrix R is taken, this row represents the correlation coefficient between the factor R_i and other factors, which is called the correlation coefficient between the single factor. The judgment matrix is usually a pairwise comparison matrix [18]. Let n factors A _ 1, A _ 2, ..., A _ n, and the importance values of each factor are nonzero values D _ 1, D _ 2, ..., D _ n, then the element value of the judgment matrix is the ratio of the importance values of each factor, as shown in formula (3).