A NEW FORECASTING-MODEL FOR AGRICULTURAL COMMODITIES

This paper presents a mathematical model for forecasting the production of some agricultural commodities. This method takes into account the general trend of the time series and random fluctuations about this trend. It has the merits of both simplicity of application and high forecasting precision. In particular, the forecast values of the model are more precise than those of other models such as the index smoothing method and the grey dynamic model, for data sequences with large random fluctuations. The case study of the silkworm cocoon production in Zhejiang province shows the merits of the model.