Optimization of Model Scheduling Algorithm in Real-Time Monitoring and Early Warning of Landslide

  Objectives  Monitoring and early warning is an important means of geohazard prevention and mitigation. In the real-time monitoring and early warning of landslide, the scheduling algorithm of early warning model is directly related to the success of early warning. The traditional way is to start the early warning service regularly, which is easy to realize and is also a common practice in the industry. However, due to the influence of the time interval, there is a certain delay in the issuance of the early warning conclusion, which cannot achieve real-time early warning. How to get early warning level quickly through early warning model and real-time monitoring data, and how to control the time and frequency of sending early warning information are two key problems to be solved.

  Methods  In order to shorten the time interval from data collection to early warning information sending, and win more time for the follow-up early warning processing, this paper studies the early warning process and model scheduling algorithm. Based on the time-driven and data-driven scheduling mode of early warning model, combined with the types and characteristics of real-time monitoring data, the scheduling strategy of early-warning model and the release strategy of early warning information are proposed to improve the warning accuracy of landslide, and a set of early warning level solver is developed.

  Results  For the early warning model scheduling of displacement monitoring data, the time-driven mode can be used in the initial stage of landslide deformation, and the data-driven mode can be used after the accelerated deformation stage. This can greatly reduce the number of early warning calculation, and ensure that the key deformation information can be captured in time. For the state monitoring data, the data-driven mode can be used for early warning to ensure the timeliness of early warning. For rainfall data, time-driven mode has a good effect. Here, the time interval can be determined by combining the data characteristics.

  Conclusions  The multi thread technology is used to construct the general computing framework of the early warning model based on strategy, to realize the real-time process tracking and early warning of landslide, and give full play to the role of landslide early warning platform. and the general computing framework of early warning model based on strategy is constructed by using multi-threading technology.