Application of Trigonometric Grey Prediction Approach to Forecasting China Grain Yield
The grain yield time series is a non-steady time series that has the definite dynamic tendency and stronger random fluctuation. Therefore, we first use the grey GM(1, 1) model to obtain the tendency term, and then the generalized trigonometric model is used to catch the periodic phenomenon from the data for improving forecasting accuracy. The grey model with the trigonometric residual modification technique, which is named trigonometric grey prediction model, has combined the advantages of grey model and the trigonometric model, it has overcome the influence by data fluctuation to precision of forecasting. At last, the validity and applicability of the model are demonstrated by a simulation of annual grain yield.
Hai-Qing Hu Dan Zhang Qiu-Ping WANG
School of Business Administration, Xi’an University of Technology, Xi’an 710054, China School of Sciences, Xi’an University of Technology, Xi’an 710054, China
国际会议
2009 IEEE International Conference on Grey System and Intelligent Services(2009 IEEE灰色系统与服务科学国际会议)
南京
英文
538-542
2009-10-20（万方平台首次上网日期，不代表论文的发表时间）