A Gray Model With a Time Varying Weighted Generating Operator
提出一种带有时变加权生成算子的灰色模型，通过增加新数据权重并减少数据波动影响，在有限数据预测中比传统灰色模型更准确可靠。
A gray model with a time varying weighted generating operator is put forward in order to fully extract information concealed in recent data. This model increases the weight of new data and reduces the influence of some possible data fluctuation. The relationship between the sample size and the error from the inverse time varying weighted generating operator is discussed. Compared with traditional gray forecasting models, the results of the practical numerical examples demonstrate that this new model performs well in forecasting problems with limited data, and provides reliable and acceptable accuracy for future prediction.