The "node anchor weaving method" is commonly used in urban rail transit network planning, which emphasizes identifying the important nodes of the network first, and then using the key nodes as the "anchor nodes" to construct the network. Interchange stations are the most crucial network nodes in terms of both service function and network function. As a result, when planning the network, it is critical to identify the interchanges ahead of time. A key node identification model is initially established in this article, and then a network interchange stations location model is built on top of it. Based on the urban road network, the key node identification model takes into account the location of the road network nodes, the number of neighboring nodes, the influence of the neighboring nodes, and the path information between the nodes, and the key nodes in the network are effectively identified through the improvement of the gravitational model and the neighboring core model, and the model's validity is verified through the SIR contagion model. The online network interchange stations siting model considers the matching degree of residents' traffic demand, the interchange stations coverage to the city, the intensity of land use, and the interchange stations' duplicate coverage to the urban space as evaluation indices for the interchange stations; the objective of solving the interchange stations is the comprehensive optimality of the indexes; in order to avoid the problem of perturbation in the optimization and solution algorithm, this paper presents an improved genetic-simulated annealing optimization algorithm that introduces the concept of community, and avoids the problem of perturbation in the optimization and solution algorithms. The effectiveness of the model is verified by using examples of the Mitte-Center and Friedrichshain networks.