Research on air conditioning load forecasting based on VMD-CIGWO-BP-DTA
A prediction model(VMD-CIGWO-BP-DTA)based on Circle Chaotic Grey Wolf Optimizer(CIGWO)optimized BP neural network combined with variational mode decomposition(VMD)was proposed to predict and analyze the load of storage air conditioning.The CIGWO algorithm is used to optimize the BP neural network model to obtain the optimal neuron threshold and weight,and the CIGWO-BP model has the highest prediction accuracy.Variational mode decomposition(VMD)was used to decompose the prediction residual of a single model,and decision tree(DTA)model was used to predict the decomposition quantity,which was combined with the predicted value of the original model into the final prediction result,and the prediction accuracy was greatly improved.MAE,MAPE and RMSE of VMD-CIGWO-BP-DTA model decreased by 20.79％,45.58％and 55.12％,respectively,compared with CIGWO-BP model.
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