To enhance the accuracy of grey forecasting models in forecasting railway passenger volume,this study proposed fitting the accumulated generating sequence of sample data with a function,followed by determining its definite integral to improve the background value within the grey forecasting model.With Shanghai's railway passenger volume serving as the subject of investigation,the efficacy of the enhanced grey forecasting model was verified.The results indicate that a grey forecasting model incorporating functional fitting of the accumulated generating sequence and the calculation of background values through definite integration exhibits superior forecast precision.Compared to conventional methods and the exponential integral approach,the proposed improvement yields average relative forecasting errors for background values reduced by 0.097%and 0.183%respectively.
grey modelbackground value improvementfunction fittingrailway passenger volumeforecast
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