## 4 Experimental Validation and Analysis
### Experimental Validation
#### 4.1.4 Comprehensive Evaluation  
Table 6 lists the evaluation grades and their corresponding scores.  
Statistical analysis of the experimental data confirmed that evaluation indicators (\(u_{11}\), \(u_{12}\), \(u_{13}\), \(\ldots\), \(u_{42}\)) follow normal distributions. Therefore, the membership matrix of each evaluation indicator relative to each evaluation level is calculated by Gaussian Membership Function Equation (68).  
\[r_{ij}=e^{-\frac{(u_{ij}-c)^{2}}{2c^{2}}} \tag{68}\]  
where \(r_{ij}\) is the membership degree of indicator \(u_{ij}\) to the \(k\)th comment level; \(c\) is the mean value; and \(c\) is the standard deviation.  
The single-factor evaluation matrices \(\mathbf{R_{1}}\), \(\mathbf{R_{2}}\), \(\mathbf{R_{3}}\), and \(\mathbf{R_{4}}\) correspond to the first-level FCEs of \(U_{1}\), \(U_{2}\), \(U_{3}\), and \(U_{4}\) are calculated by Equation (42), respectively.  
\[\mathbf{R_{1}}=\begin{bmatrix}0.004&0.644&0.37&0&0\\ 0.24&0.75&0.98&0.52&0.27\\ 0&0.169&0.89&0.018&0\\ 0&0.64&0.37&0&0\end{bmatrix} \tag{69}\]  
\[\mathbf{R_{2}}=\begin{bmatrix}0&0.018&0.78&0&0\\ 0&0.06&1&0.06&0\\ 0.79&0.37&0.018&0&0\\ 0.004&0.644&0.37&0&0\end{bmatrix} \tag{70}\]  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Grades** & **Best** & **Better** & **Good** & **Normal** & **Bad** \\ \hline Score & \(\geq\)0.9 & \([0.7,0.9)\) & \([0.5,0.7)\) & \([0.3,0.5)\) & \(<\)0.3 \\ \hline \hline \end{tabular}
\end{table}
Table 6: Comprehensive evaluation grades definition.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**The EMC Performance of Vehicle Wireless Communication System** & \(\boldsymbol{U_{2}}\) & \(\boldsymbol{U_{1}}\) & \(\boldsymbol{U_{3}}\) & \(\boldsymbol{U_{4}}\) \\ \hline \(U_{2}\) & 1 & 2 & 3 & 2 \\ \(U_{1}\) & 1/2 & 1 & 1/3 & 1 \\ \(U_{3}\) & 1/3 & 3 & 1 & 2 \\ \(U_{4}\) & 1/2 & 1 & 1/2 & 1 \\ \hline \hline \end{tabular}
\end{table}
Table 5: Criterion level index.  
\[\mathbf{R}_{3}=\begin{bmatrix}0.779&1&0.779&0.37&0.105\\ 0.018&0.37&1&0.37&0.018\end{bmatrix} \tag{71}\]  
\[\mathbf{R}_{4}=\begin{bmatrix}0.002&1&0.002&0&0\\ 0.64&0.37&0.001&0&0\end{bmatrix} \tag{72}\]  
The first-level FCE sets \(\mathbf{B}_{1}\), \(\mathbf{B}_{2}\), \(\mathbf{B}_{3}\), and \(\mathbf{B}_{4}\) are calculated using Equations (16), (44), and (62)-(65), respectively.  
\[\mathbf{B}_{1}=[0.096,0.56,0.74,0.213,0.108] \tag{73}\]  
\[\mathbf{B}_{2}=[0.238,0.32,0.472,0.012,0] \tag{74}\]  
\[\mathbf{B}_{3}=[0.475,0.748,0.867,0.37,0.016] \tag{75}\]  
\[\mathbf{B}_{4}=[0.321,0.685,0.002,0,0] \tag{76}\]  
The single-factor evaluation matrix \(\mathbf{R}\) (Equation (77)) for the two-level FCE is derived from Equations (45) and (66)-(69).  
\[\mathbf{R}=\begin{bmatrix}0.096&0.56&0.74&0.213&0.108\\ 0.238&0.32&0.472&0.012&0\\ 0.475&0.748&0.867&0.37&0.016\\ 0.321&0.685&0.002&0&0\end{bmatrix} \tag{77}\]  
The two-level FCE set \(\mathbf{B}\) (Equation (71)) is obtained by combining Equations (47), (60), and (70).  
\[\mathbf{B}=[0.417,0.148,0.278,0.157]\bullet\left[\begin{array}{ccccc}0.096& 0.56&0.74&0.213&0.108\\ 0.238&0.32&0.472&0.012&0\\ 0.475&0.748&0.867&0.37&0.016\\ 0.321&0.685&0.002&0&0\end{array}\right] \tag{78}\]  
\[=(0.258,0.582,0.60,0.193,0.049)\]  
Based on the calculation results of Equation (78), Table 7 lists the detailed evaluation scores.