Dynamic Inspection Planning for River Water Conservancy Facilities Based on Coupled Risk Warning and Genetic Algorithm

For planning river inspection routes, the traditional method relies heavily on the experience of workers to select inspection sites and plan routes for river water conservancy facilities, which may lead to insufficient coverage of inspection sites and delayed identification of issues with these facilities. Therefore, it is necessary to develop a new method for planning river inspection routes that can achieve broader coverage and more efficient inspection in river water conservancy facilities with potential hazards. This paper proposes a method based on a coupled risk warning-genetic algorithm to establish a risk warning model for river water conservancy facilities and a route planning model for river inspections, thereby achieving the planning of inspection routes for river water conservancy facilities. The risk warning model in this paper calculates the risk levels of the inspection targets using the entropy weight-Topsis method. By coupling a genetic algorithm-based route planning model for river inspections, the risk warning model uses these risk levels as input data for the route planning model, ultimately determining the routes for river inspections. Daily river inspections conducted by the Guangzhou River Monitoring Center have proven that the proposed method provides more reasonable routes than the traditional method, performing better in terms of coverage and efficiency in inspecting potential hazards.