## 3 Case Study
### Result Analysis
#### 3.3.1 Hierarchical Evaluation of Node Importance Based on Single Indicators
In Figure 6, a detailed computational analysis of the DC network is presented, highlighting variations in key indicators across different nodes:  
* The CS curve exhibits high values on the left and right ends, indicating that nodes within the station throat play a dominant role in network connectivity. However, the presence of low-ranking nodes within the throat areas suggests structurally weaker connections, which may limit operational flexibility and impact overall efficiency;
* The DNC and SNC curves demonstrate significant fluctuations, reflecting the varied roles of nodes in network connectivity. Peaks in DNC and SNC rankings highlight highly influential nodes, likely corresponding to key junctions connecting arrival and departure areas. In contrast, nodes in the central region generally exhibit lower DNC and SNC values, indicating that they primarily function as intermediate links rather than major operational hubs;
* The NE values show considerable variation, likely due to differences in node centrality and link availability across the network. The station throat areas display relatively high NE values, reinforcing their critical role in maintaining network efficiency. However, localized drops in NE indicate potential bottlenecks or inefficiencies, where certain nodes may be underutilized or susceptible to congestion under specific conditions;
* Compared to the other indicators, the EPR curve exhibits a more volatile trend, highlighting its strong sensitivity to network topology. The high EPR values in the throat areas confirm that these nodes possess significant structural importance, playing a key role in train movements. However, the presence of low-ranking nodes within the throat suggests that not all nodes contribute equally to the overall network significance, emphasizing the need for strategic optimization of these areas. Overall, despite variations among individual metrics, all five parameters consistently confirm that the upward and downward throat areas contain higher-ranked nodes than the central region, reinforcing their critical role in railway yard operations. The existence of low-value nodes within the throat areas underscores structural disparities, revealing potential opportunities for capacity enhancement and operational improvements. This analysis highlights the necessity of optimizing specific nodes to enhance the overall efficiency and reliability of railway operations. The summary of the analysis results for the three networks is presented in Table 2.  
To gain a comprehensive understanding of node importance within the station topology network, the computation results for each layer are presented in the corresponding figures and summarized in the table above. The figures depict the spatial distribution of node importance under various parameters, while the table provides a concise comparison of the most critical nodes identified for each parameter across the three networks. The results reveal notable differences in node importance rankings across different parameters. In the LC network, rankings vary significantly, with certain nodes consistently showing lower importance across all metrics, indicating relatively weak significance. The YX network exhibits a pronounced bimodal distribution, where nodes on the left side are generally more important than those on the right, attributed to the inclusion of TSs in the downward throat area. In contrast, the DC network demonstrates higher importance for nodes on the left and right sides compared to central nodes. Additionally, the node rankings in the DC network are more consistent across parameters, reflecting the structural characteristics of the upward and downward throat areas. The node importance analysis for different network layers is closely related to the scale of nodes covered by the interlocking table routes, with parameter selection significantly influencing node rankings. While no single node is consistently the most important across all metrics, certain nodes consistently rank lowest, indicating minimal relative importance.