Application of SSA-RBF Neural Network Model in Wind Power and Wind Speed Prediction
In order to improve the accuracy and stability of wind power prediction to better cope with the variabil-ity and nonlinear characteristics of wind speed,this paper proposes a wind speed prediction model(SSA-RBFN)based on the SSA optimized radial basis function(RBF)neural network.The parameters of RBFN are optimized by SSA to predict and improve the accuracy and stability of the model.By selecting actual data from wind farms for the study and comparing with SSA-BP model,RBF model,and BP model,the simulation results show that the SSA-RBF prediction model is reflected in the MAE,MBE,and RMSE indexes,and the prediction error is signifi-cantly lower than that of the traditional RBF and BP models,which indicates that the proposed model is feasible and effective.
wind speed predictionsparrow search algorithmradial basis function neural networkprediction model optimization
万方数据
维普
