Improvement of Threshold Auto-regressive Model Based on Genetic Algorithm and Its Application
Jin Guang-qiu · Journal of Yangtze River Scientific Research Institute · 2006
Because fitted effect of threshold auto-regressive(TAR) model is sometimes better than its predicted effect,or predicted effect is bad,TAR is improved,i.e.,when time series x(i) are fitted and predicted,AR's observed values of half period besides i are replaced by calculated values of fit or forecasting of TAR model.By depicting the figure of auto correlation coefficients,it may ascertain clearly delayed paces and ranks of the auto-regressive model of threshold sections. The result of an example shows its improvement can enhance stability and practicability of the model and application of TAR in security supervision forecast is effective and successful.