AN IMPROVED ALGORITHM FOR DYNAMIC DATA SYSTEM MODELING

Disadvantages of the traditional Dynamic Data System modoling method is first briefly described. The way to improve it is explained and the improved algorithm derived. Detailed block diagrams of the improved algorithm are given.First, a long AR model is used to fit the data untill the residuals are simply white noise. If the order of AR model is not high, the AR model is recognized.0therwhise,using the data and the residuals,the ARMA model parameters can be estimated by means of the linear Least Square Method. The coefficient matrices of Yule-Wolker equation and the model parameters can be recurrently calculated when the model order is increased or decreased. When preliminary estimation of suitable ARMA model is obtained, the nonlinaar Least Square method is used to optimize the para-meters.Two simulated examples are given and the results show that the improved modeling method can save ca.66%in time of computation attaining with the same precision.lt can be taken that the improved algorithm is a successful one.