RBF Neural Network Prediction Model Based on Particle Swarm Optimization for Internet-Based Teleoperation

For Internet based real-time teleoperation systems, the exact prediction of round trip timedelay (RTT) can have great importance on teleoperation systems performance. In order to solve Internet delay prediction problem, this paper proposes an improved radial basis function (RBF) neural network prediction model. In this model, which is different from other traditional prediction models, is that local particle swarm optimization algorithm is used to adjust RBF network parameters and binary particle swarm optimization algorithm is used to adjust structure of RBF model. Based on this idea, we propose the improved RBF neural network prediction model, and we use this model to make prediction of Internet delay. The experiment result shows that this model is effective.