# Research on a Comfort Evaluation Model for High-Speed Trains Based on Variable Weight Theory
## 4 Engineering Examples
### Fuzzy Comprehensive Score and Result Analysis
\begin{table}
\begin{tabular}{c c c c c c c c c c c c c} \hline \hline \multirow{2}{*}{\(\text{B}_{1}\)} & \multirow{2}{*}{\(\text{W}_{\text{i}}\)} & \multirow{2}{*}{\(\text{C}_{\text{ij}}\)} & \multirow{2}{*}{\(\text{W}_{\text{i}}\)\({}^{\text{0}}\)} & \multicolumn{1}{c}{**Constant Weight**} & \multicolumn{1}{c}{**Variable Weight**} & \multicolumn{1}{c}{**Weight**} & \multicolumn{1}{c}{**Confort Grade**} & \multicolumn{1}{c}{} \\  & & & **Comprehensive** & \(\text{x}_{\text{ij}}\)\({}^{\text{0}}\) & & **Comprehensive** & \(\text{Range}\) & **Change** & **I** & **II** & **III** & **IV** & **V** \\  & & & & **Weight** & & & **Weight** & & **Rate/\%** & **I** & **II** & **III** & **IV** & **V** \\ \hline \multirow{4}{*}{\(\text{B}_{1}\)} & \multirow{4}{*}{0.4599} & C\({}_{11}\) & 0.1129 & 0.0520 & 90.00 & 0.1126 & 0.0518 & \(-\)0.38 & 0.00 & 1.00 & 0.00 & 0.00 & 0.00 \\  & & C\({}_{12}\) & 0.0515 & 0.0237 & 91.38 & 0.0509 & 0.0234 & \(-\)1.27 & 0.14 & 0.86 & 0.00 & 0.00 & 0.00 \\  & & C\({}_{13}\) & 0.4178 & 0.1921 & 89.19 & 0.4199 & 0.1931 & 0.52 & 0.00 & 0.96 & 0.04 & 0.00 & 0.00 \\  & & C\({}_{14}\) & 0.4178 & 0.1921 & 89.88 & 0.4166 & 0.1916 & \(-\)0.26 & 0.00 & 0.99 & 0.01 & 0.00 & 0.00 \\  & & C\({}_{21}\) & 0.4440 & 0.1323 & 86.50 & 0.4467 & 0.1332 & 0.68 & 0.00 & 0.83 & 0.18 & 0.00 & 0.00 \\  & & C\({}_{22}\) & 0.2401 & 0.0716 & 88.75 & 0.2377 & 0.0709 & \(-\)0.98 & 0.00 & 0.94 & 0.06 & 0.00 & 0.00 \\  & & C\({}_{23}\) & 0.0422 & 0.0126 & 86.88 & 0.0424 & 0.0126 & 0.00 & 0.00 & 0.84 & 0.16 & 0.00 & 0.00 \\  & & C\({}_{24}\) & 0.1059 & 0.0316 & 87.56 & 0.1057 & 0.0315 & \(-\)0.32 & 0.00 & 0.88 & 0.12 & 0.00 & 0.00 \\  & & C\({}_{25}\) & 0.1678 & 0.0500 & 87.63 & 0.1675 & 0.0499 & \(-\)0.20 & 0.00 & 0.88 & 0.12 & 0.00 & 0.00 \\  & & C\({}_{31}\) & 0.3532 & 0.0396 & 90.75 & 0.3503 & 0.0392 & \(-\)1.01 & 0.08 & 0.93 & 0.00 & 0.00 & 0.00 \\ \multirow{2}{*}{\(\text{B}_{3}\)} & \multirow{2}{*}{0.1120} & C\({}_{32}\) & 0.3192 & 0.0357 & 89.00 & 0.3215 & 0.0360 & 0.84 & 0.00 & 0.95 & 0.05 & 0.00 & 0.00 \\  & & C\({}_{33}\) & 0.1020 & 0.0114 & 88.88 & 0.1027 & 0.0115 & 0.88 & 0.00 & 0.94 & 0.06 & 0.00 & 0.00 \\  & & C\({}_{34}\) & 0.2256 & 0.0253 & 89.88 & 0.2255 & 0.0253 & 0.00 & 0.00 & 0.99 & 0.01 & 0.00 & 0.00 \\  & & C\({}_{41}\) & 0.6955 & 0.0314 & 89.13 & 0.6980 & 0.0315 & 0.32 & 0.00 & 0.96 & 0.04 & 0.00 & 0.00 \\  & & C\({}_{42}\) & 0.0755 & 0.0034 & 89.19 & 0.0758 & 0.0034 & 0.00 & 0.00 & 0.96 & 0.04 & 0.00 & 0.00 \\  & & C\({}_{43}\) & 0.2290 & 0.0103 & 91.0 & 0.2262 & 0.0102 & \(-\)0.97 & 0.10 & 0.90 & 0.00 & 0.00 & 0.00 \\  & & C\({}_{51}\) & 0.1549 & 0.0131 & 83.25 & 0.1577 & 0.0134 & 2.29 & 0.00 & 0.66 & 0.34 & 0.00 & 0.00 \\  & & C\({}_{52}\) & 0.2631 & 0.0223 & 84.94 & 0.2633 & 0.0224 & 0.45 & 0.00 & 0.75 & 0.25 & 0.00 & 0.00 \\ \multirow{2}{*}{\(\text{B}_{5}\)} & \multirow{2}{*}{0.0849} & C\({}_{83}\) & 0.4130 & 0.0351 & 86.31 & 0.4100 & 0.0348 & \(-\)0.85 & 0.00 & 0.82 & 0.18 & 0.00 & 0.00 \\  & & C\({}_{54}\) & 0.0732 & 0.0062 & 87.25 & 0.0721 & 0.0061 & \(-\)1.61 & 0.00 & 0.86 & 0.14 The Table 6 calculation results show that intuitively from the rating interval, regardless of constant weight state or variable weight state, the Tongwei-Lanzhou section of the Baolan passenger-dedicated line has a high-speed train comfort evaluation result of grade II. This is consistent with the recent evaluation results of the management unit. At the same time, the fuzzy comprehensive score of each first-level index also shows that the operating performance, noise and pressure, air quality, vehicle decoration environment, and personalized service comfort of the section are also grade II in both cases. However, the score obtained by using variable weight theory is always lower than that of constant weight fuzzy calculation. This shows that the introduction of variable weight theory makes the adjustment and optimization of state value on constant weight receive attention.