Treatment of time series instability - review article-
Abstract
the time series is a problem in econometric analysis as the statistical properties of series analysis are lost when using unstable time series. The research aims to present several methods for dealing with stability, including (Box Jenkins, Exponential Smoothing, Double Exponential Smoothing, Exponential Smoothing Moving Averages, Fuzzy, Neural Network) and to compare the methods presented through diagnosing ARIMA models after achieving stability and choosing the best method that corresponds to the lowest values of the criteria Statistics (MSE, AIC, BIC). The above-mentioned methods have been applied to daily data for the year 2020 to generate electricity from water coming from the Tigris River, and it was concluded that the (Fuzzy) method is the best for treating stability compared to other methods for having the ARIMA model (0,1,3) corresponding to the lowest values of the criteria Statistics (MSE=0.572, AIC=-196.4536, BIC=-0.6931).
References
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