AR model parameter estimation based on particle swarm optimization algorithm
Using the particle swarm optimization algorithm to optimize the AR (P) model parameters, improve the prediction accuracy of the model .The AIC criterion can determine the best order number of the model.This estimation method is superior to the traditional estimation based on least squares estima-tion and gray theory estimation .The estimated parameters provides a new way of thinking for the parame-ter estimation of this kind of model .
NETL
NSTL
万方数据
维普
