## 5 Conclusions and Prospect  
Based on the complex network theory, we analyzed the characteristics of the Beijing subway network and gave the method of key lines' identification. The main conclusions and research outlook are as follows. 1. The current Beijing subway network under Space L, the cumulative distribution of degree conforms to the logarithmic function distribution, and the goodness of fit \(R^{2}\) = 0.8531, which is a scale-free network, but with low aggregation coefficient and no small-world characteristics. Under Space P, the goodness of fit \(R^{2}\) = 0.9391 for the logarithmic function, and with high clustering coefficient, low network diameter, strong small-world characteristics, and scale-free network. Under Space C, the goodness of fit \(R^{2}\) = 0.9166 for the logarithmic function, with scale-free network characteristics and similar to Space L network, it has low aggregation but long distance and no small-world network characteristics;
2. By establishing the line importance index system and giving the key lines' identification method, based on the Matlab simulation experiment, we obtained the criticality of each line, which Line 1, Line 2, Line 4, Line 6, and Line 10 are the five subway lines with the highest criticality under Space L and Space P; and
3. Considering the global and local levels, different analysis indexes reflect the different image degrees of the lines to the global network and subway lines, and there are unit differences between the indexes. The line importance index \(L_{u}^{inp}\) is proposed to combine the above indexes to derive the criticality of the line at a comprehensive level. Considering only the complex network characteristics, Line 10, Line 9, Line 1, Line 2, and Line 5 are the five most important subway lines, with line importance indexes of about 10.07, 6.48, 5.06, 4.56, and 4.36. Line S1, Changping Line, Xijiao Line, Capital Airport Line, and Daxing International Airport Line are the five lowest-importance subway lines, with line importance indexes of about 1.04, 1.04, 0.94, 0.31, and 0.25. More and more cities are stepping into subway construction, and the scale and structure of subway networks are showing complexity. This study characterizes the current network of the Beijing subway network, but the future characteristics will be changed. Previous scholars have less involvement in the network characteristics under Space C. This study initially involves the small-world and scale-free characteristics of the subway network under Space C, and other studies need to be further deepened, such as association analysis. At the same time, the key lines' identification method selected in this study, for the selection of indexes, can be further improved. Space C, also known as an interchange network, expresses the connection between lines and can be introduced into the key lines' \begin{table}
\begin{tabular}{c c c c c} \hline
**Subway Lines** & **Importance Index** & **Ranking** & **Subway Lines** & **Importance Index** & **Ranking** \\ \hline Line 10 & 10.073 & 1 & Line 14 East & 2.159 & 13 \\ Line 9 & 6.479 & 2 & Line 7 & 1.922 & 14 \\ Line 1 & 5.059 & 3 & Yizhuang Line & 1.734 & 15 \\ Line 2 & 4.558 & 4 & Line 15 & 1.246 & 16 \\ Line 5 & 4.362 & 5 & Line 16 & 1.129 & 17 \\ Fangshan Line & 4.361 & 6 & Line 8 North & 1.109 & 18 \\ Line 4 & 3.461 & 7 & Batong Line & 1.098 & 19 \\ Line 6 & 3.155 & 8 & Line S1 & 1.042 & 20 \\ Line 14 West & 2.505 & 9 & Changping Line & 1.035 & 21 \\ Line 13 & 2.48 & 10 & Xijiao Line & 0.942 & 22 \\ Yanfang Line & 2.225 & 11 & Capital Airport Express & 0.312 & 23 \\ Line 8 & 2.169 & 12 & Daxing International Airport Express & 0.25 & 24 \\ \hline \end{tabular}
\end{table} 
Table 12: Line importance index of Beijing subway. identification. The centrality sensitivity coefficient is proposed to describe the sensitivity of the lines to the influence of other networks, which is not overly developed, but this study provides direction for the study of network robustness, which is one of the directions of future research. Conceptualization, Y.P.