3D Digital Transmission Line Path Planning Method Based on Cloud Platform

Different categories of data such as terrain, climate, and geology are processed separately in existing path planning, making it difficult to integrate and analyze them in a unified environment. The lack of a unified platform to integrate these data results in path planning being unable to consider multiple influencing factors simultaneously, reducing the scientific and practical nature of the planning. This article constructs a 3D digital transmission line model based on a cloud platform, which can integrate and process real-time multi-source data such as terrain, climate, and geology in the cloud, and convert it into a digital form that can be processed and analyzed in a computer. Based on the above information, a digital cost evaluation model is constructed, and the model is equivalent to a weighted grid matrix. Then, the Particle Swarm Optimization (PSO) method in data mining is introduced for path planning. The optimal path is found by simulating the social behavior of bird flocks, and the behavior of path planning in the environment is guided by learning information sharing and collaboration among individuals in the group. By comparing experimental data, it was found that the PSO algorithm has a minimum convergence time of only 100 ms in transmission line path planning, and the total cost in 30 path planning projects is 84.76 million yuan, significantly lower than the cost of GA and SA algorithms. This indicates that PSO algorithm outperforms GA and SA algorithms in both speed and cost control.