The flow prediction model in Internet of Things based on Bayesian and causal ridge regression

Abstract:

In order to solve the flow prediction problem of Internet of Things, a flow In order to solve the flow prediction problem of Internet of Things， a flow prediction model is proposed based on Bayesian and causal ridge regression.At first，the local characteristic of flow is deeply depicted considering the causal relationship between the fluctuation of the traffic flow and the change of the link;in addition, Schrodinger equation is used to optimize the recognition model.Then，the prediction model is built with Bayesian and causal ridge regression.Finally，the performance of this model and other methods is studied by simulation experiment.The results show that this model has a great advantage in average queue，blocking rate，delay rate and so on.