The whole process control algorithm of inflatable dustproof shed construction in substation engineering based on graph neural network

Abstract During the construction of an inflatable dust-proof shed in substation engineering, it is one of the key issues in power system research to use scientific whole-process control algorithms to complete substation engineering decisions. At present, the control algorithm has some problems, such as low control accuracy and poor convergence speed. Therefore, the whole process control algorithm of inflatable dust shed construction in substation engineering based on a graph neural network is proposed. The control indexes of the whole process of inflatable dust-proof shed construction in substation engineering are divided into the highest level, the middle level, and the lowest level. The discriminant matrix is established to obtain the single-factor fuzzy evaluation matrix of the middle-level index. Thus, the control indexes are constructed. According to this index, the basic operation flow of the graph neural network is constructed, the objective function of the graph neural network is set, the control steps of the whole process of inflatable dust-proof shed construction in substation engineering is analyzed, and the algorithm research is realized. The experimental results show that the convergence steps are greatly reduced, the control accuracy is high, and the convergence speed is significantly improved after applying the algorithm proposed in this paper.