Abstract: Estimating parameters of auto-regressive mov-ing-average(ARMA) model is the focus of ARMA. The disad-vantages of least-squares algorithm and its generalization algo-rithm which are used in estimating parameters of ARMA are aimed at. Simulated annealing genetic algorithm based on hy-brid optimization strategy is used in estimating parameters of ARMA and it can overcome the disadvantages of the traditional methods. Based on the new algorithm, a new method of model-ing ARMA is presented by determinating the autoregressive orders p and moving-average orders q in ARMA model. Finally, the precision data ARMA model of a mechanical system is built by the new technology and by the traditional modeling method. The new technology proves effective and high-precision by comparing the two models.

Key words: Auto-regressive moving-average(ARMA) model, Hybrid optimization strategy, Simulated annealing genetic algorithm