基于灰色理论的小样本振荡序列区间预测建模方法

传统单变量灰色预测模型的指数结构形式制约了其对小样本振荡序列的模拟与预测能力, 对此, 通过包络线将振荡序列拓展为具有明确上界与下界的区间灰数序列, 还原影响因素不确定性条件下振荡序列的区间灰数形式; 在此基础上, 利用区间灰数建模方法实现对振荡序列取值范围的模拟与预测. 应用该方法较好地模拟了具有振荡特征的重庆市空气质量指数(AQI) 的变化规律, 所得研究成果为小样本振荡序列的模拟与预测提供了一种新的分析方法与建模手段.

Modeling method of interval prediction for oscillation sequence with poor samples based on grey theory

The exponential construction form of the traditional grey prediction model with single variable restricts its simulative and predictive abilities for the oscillation sequence with poor samples. Therefore, an oscillation sequence is expanded to an interval grey number sequence with the defined upper and lower bounds through envelope lines, which restores the interval grey number form of oscillation sequence under the condition of uncertain influence factors. After this, the value ranges of oscillation sequence are simulated and forecasted by using the modeling method of forecasting interval grey number. Finally, the proposed method is employed to effectively simulate the change laws of Chongqing air quality index(AQI). The study results provide a novel analysis method and modeling tool for the oscillation sequence with poor samples.