Artificial Intelligence Control Simulation of Variable Structure Node Position in High Speed Network

With the development of high-speed network applications, the optimization of variable structure node position control plays an important role. However, at the same time, the node position control has a large energy consumption problem, which needs further detection. Therefore, this paper proposes a control scheme based on the fusion of particle swarm optimization algorithm and metropolis acceptance criteria. Based on this, a variable structure node position control model of highspeed network is constructed, and makes an in-depth analysis. Then through the simulation experiment, it shows that the highspeed network variable structure control method based on artificial intelligence is very effective and can reduce the energy consumption effectively, which has a more important reference value for the network industrial structure.