# A Network Analysis-Based Approach for As-Built BIM Generation and Inspection
## 4 Experiment
### Network Analysis  
#### 4.3.1 Global Analysis  
The characterisation of the network's properties is crucial to understanding its structure and performances, while attributes listed in Table 1 have been selected for global matching analysis. The numbers of nodes and edges are fundamental descriptors that provide a basic overview of the network's size and connectivity. Network density quantifies the extent to which the nodes in a network are interconnected and is defined as the ratio of the number of observed edges to the maximum possible number of edges. Network transitivity refers to the tendency of nodes in a network to be connected to other nodes that are themselves connected, forming triangular structures or cycles, which means the measurement of the likelihood that two nodes that share a common neighbour will also be directly connected to each other. The average shortest path length is another essential metric that captures the average number of steps required to traverse between any two nodes in a network, while the network diameter refers to the maximum distance between any two nodes in the network. The average clustering coefficient, which is a measure of the degree to which nodes in a network tend to cluster together, is another key property that can be used to infer the network's modularity or community structure. Additionally, the average degree is a measure of the average number of edges or connections that a node has in a network, and modularity is a measure of the degree to which a network can be divided into smaller, densely connected groups or communities, which is a useful metric  
Figure 10: As-designed network. for identifying clusters or subgroups within a network and can provide insight into the structure and function of the network. Table 1 indicates that while the values of each parameter in the two networks are similar, they exhibit notable differences, highlighting distinctions between as-built and as-designed BIM. The numbers of nodes and edges are two core network attributes, representing the fundamental overview of the network structure. The node count is critical for analysing the accuracy of scanning processes and segmentation algorithms. Due to limitations in scanning devices, the segmentation of building structures typically differs between the as-designed and as-built models. Generally, the as-designed model contains a higher number of nodes because scanners often fail to accurately distinguish connected wall parts, erroneously merging distinct walls into a single entity. However, in this case, the as-built model exhibits a higher number of nodes, indicating that the segmentation algorithm used during reconstruction is overly aggressive, splitting many single walls into separate structures. This insight is vital for refining and improving the algorithm. Additionally, in this experiment, a coincidental situation arises where the number of edges remains the same despite differing node counts. It indicates that as-built BIM generates numerous new connections while also losing many original links compared to as-designed BIM. New links typically form between newly added nodes due to incorrect segmentation of the same structure. The missing links are due to the situation shown in Figure 6. For connection components, as-designed BIM typically consists of numerous elements, whereas as-built BIM often recognizes these elements as a single entity, resulting in the disappearance of original links. This part is often a structural combination with a high network density. By analysing the performance of nodes and edges, it becomes evident that the connection structure of as-built BIM is relatively simple. This simplicity is attributed to its sparser network, where a greater number of nodes have an equivalent number of edges. This observation underscores the necessity for enhancing the reconstruction of as-built BIM, particularly for complex design components.