Problems existing in ARIMA model of hydrologic series and some improvement suggestions
Longxia Qian · Systems Engineering - Theory & Practice · 2008
The ARMIA model is often used for calculating time series data formed by interannual variation with a month as unit.However,the influence brought about by inter-monthly variation with a year as unit is neglected.Based on the monthly data classified by cluster,the characteristics are extracted.The correlation between characteristic quantity and monthly data with a year as unit is constructed by regression analysis.To apply stationary treatment for characteristic quantity time series by difference,the ARMIA model is adopted for predicating characteristic quantity according to class.Therefore,a new method of data mining is put forward.An improved ARMIA model is developed and used for hydrological predication.The model is applied in Lanzhou precipitation station,and the result shows that the precision of the improved model is significantly higher than the seasonal model,the mean residual achieves 9 41,and the forecast precision is increased by 21%.Finally,some discussions about the application of the improved model are given.