## 2 Literature Review  
Node importance evaluation has been a hot research topic in the field of urban rail transport. In recent years, scholars have conducted some case studies on the evaluation of the importance of nodes in real rail networks. [PERSON] et al. [16] evaluated the importance of urban rail nodes using the London Underground network as a practical example. [PERSON] et al. [17] conducted a comprehensive evaluation of the rail lines of the Republic of Turkey State Railways (TCDD). [PERSON] et al. [18] used the metro network in Suzhou, China, to evaluate the node importance of the metro network. In terms of evaluation indices, scholars initially selected node degree [19], facility service level [20], and other factors to evaluate rail transit stations from a local perspective. Subsequently, some scholars adopted the complex network theory from a global perspective, using node degree centrality, betweenness centrality, closeness centrality [21; 22], and other indicators to evaluate the importance of nodes in static urban rail transit networks [23; 24]. The evaluation method can only reflect the performance of the network when it is in a stationary state (that is, under normal operation), and cannot reflect the change in the network state of urban rail transit in actual operation. For example, the degree can only reflect the distance between nodes, and the degree of centrality can only reflect the existence of connecting edges between nodes. However, the urban rail transit network is dynamically changing in actual operation, and considering the actual operation of rail transit, some studies have introduced the network interdiction model [25], which simulates the network failure by removing nodes and edges in the network. The network interdiction model was first introduced for military purposes, intending to identify and determine the most critical set of arcs in a network [26; 27], and has subsequently been extended to the domain of complex networks, such as electric power networks [28], wireless sensor networks [29], and rail transit networks [25]. Combined with the actual operation of rail transit, the existing research constructed a node importance evaluation system based on the dynamic perspective, selecting indicators such as average network efficiency [30], maximum connectivity subgraph change [31], network efficiency accessibility [32; 33], and unsatisfied passenger demand [34; 35] from the aspects of network topology and network operation performance. Then, the network interdiction model was used to carry out station failure simulations in urban rail transit networks to carry out network node importance evaluations and key station identification. In terms of network failure mechanisms, most of the studies only remove the failed station itself and its connected lines from the network when simulating station failure [25; 36], while a few studies improve the failure mechanism by taking into account the actual characteristics of the rail network and disruption scenarios. [PERSON] et al. [37] considered that urban rail transit operates on specific routes, used spatial syntax to analyze the line accessibility of rail transit to improve the topological network, and proposed the node importance evaluation method. [PERSON] et al. [38] incorporated the adjustment of train operation interchanges after station failure to evaluate the importance of rail transit stations in the scenario of bidirectional operation disruption. [PERSON] et al. [39] proposed a weighted multi-layer network node importance evaluation method that considers node connectivity, diverse transportation modes, and service capabilities. [PERSON] et al. [40], combined with the unexpected situations encountered in the actual operation of public transport, considered two types of attacks against the bus-subway composite network nodes for node importance evaluation research.