Application Load prediction model based on SA-IPSO-BiLSTM

In order to solve the problem of low accuracy in application load prediction, this paper proposes an application load prediction model based on SA-IPSO-BiLSTM. Firstly, the model puts the data into the BiLSTM neural network for training and uses the adaptive algorithms to automatically adjust the parameters of the BiLSTM neural network. Then, an improved particle swarm optimization algorithm is used to optimize the parameters of the BiLSTM neural network. Finally, the optimized BiLSTM is used for the application load prediction. Comparison with the existed prediction models, the result demonstrates that the SA-IPSO-BiLSTM model has a higher accuracy and strong applicability in application load prediction.