Integrated Prediction of GM(1,1)-Exponential Smoothing Combination and Grey Interval Oscillation Series——Take the Future Development Trend of Flexible Employment Youth as an Example
By constructing the grey GM(1,1)-cubic exponential smoothing model and grey in-terval GM(1,1)model,this paper comprehensively predicts the number of flexible employment youth in urban areas.Firstly,the inverse variance method is innovatively used to construct the GM(1,1)-cubic exponential smoothing model.The average absolute error and average relative error of the model are minimized,and the prediction accuracy is improved.Secondly,accord-ing to the characteristics of small sample oscillation series,a relatively perfect grey interval GM(1,1)model is constructed,which significantly improves the prediction accuracy.Finally,this paper forms a framework for estimating the number of flexible employment in urban ar-eas and the number of flexible employment youth based on"informal employment rate",and establishes a GM(1,1)-cubic exponential smoothing model and a grey interval GM(1,1)model for the number of flexible employment and the number of flexible employment youth based on the introduction of the elderly population coefficient.The GM(1,1)-exponential smoothing model and the grey interval GM(1,1)model are cleverly integrated to obtain the final pre-dicted value.The results show that the predicted value is in good agreement with the real value,and the comprehensive processing of multiple sets of data is realized.
the number of flexible employment youthGM(1,1)-cubic exponential smoothinggrey interval GM(1,1)model
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