Topological Mapping and Risk Assessment of High Slope Engineering Deformation Time Series from the Perspective of Complex Network

With the continuous expansion of infrastructure coverage, road foundation projects are gradually moving to remote mountainous areas, and the number of high side slope projects is gradually increasing, which will inevitably damage the geological structure during construction and may cause safety problems such as landslides and slope instability. The traditional methods of high slope deformation risk assessment are to assess the high slope deformation risk by comparing the difference between the accumulated deformation value and the industry standard, but such methods are difficult to accurately identify the location and changes of deformation risk and are not accurate enough. This research proposes a complex network method based on time series to analyze and assess the risk of high slope deformation from a systematic perspective based on deformation data, and addresses the limitations of traditional methods. The raw time series of slope surface deformation instrumentation data during construction were measured into a similarity matrix with correlation coefficients. A threshold was then determined and binarized into adjacent matrix to identify the optimal topology and structure of the complex network. Finally, the statistical features of complex networks are applied to describe the deformation risk distribution of high side slopes. A high slope project case of China's Menghua coal transportation railroad was applied to verify the effectiveness and feasibility of the proposed approach. Results demonstrated that the proposed approach confirms the small-world and scale-free characteristics of high slope deformation processes and evaluates the significance among high slope deformation time series. This approach can be a tool for extracting macroscopic and microscopic decision information from complex systems perspective for high slope multi-deformation time series. It not only offers a systematic way to interpret deformation risk of slope environment in high slope construction but also has the potential to improve safety performance in construction sites.