Temperature prediction of sintering machine head based on improved time series model
Aultra short term temperature prediction model based on WD-ARIMAX-GARCH is adopted to address the serious impact of abnormal temperature changes in the sintering machine head on the quality of sintered ore.Due to the frequent influence of external factors on temperature time series,and the fact that time series models(ARIMA)only regress historical time series and cannot reflect the impact of external factors,exogenous variables(ARIMAX)are added.By introducing wavelet decomposition(WD),the temperature time series is decomposed into several sub sequences,and residual sequence tests are performed on each component.ARIMA-GARCH models are established for components with heteroscedasticity characteristics,and the predicted results are combined with the decomposed data as exogenous variables for re prediction.The results indicate that the temperature prediction method based on WD-ARIMAX-GARCH model has high accuracy.
temperature forecastexternal variableARIMA-GARCH modelwavelet decomposition
万方数据
维普
