最优非负变权组合模型在卫星钟差预报中的应用

针对单一卫星钟差预报模型自身存在的缺陷，提出基于二次多项式、灰色GM（1，1）和ARIMA等三种单一模型的最优非负变权组合预报模型。通过与各单一模型和经典权组合模型进行对比分析表明，该模型预报残差RMS值最小，精度更高，能够根据各模型预报效果赋予不同的权值，在一定程度上综合了多种单一模型的优点，可降低预报风险，提高模型预报的可靠性。

Application of the Optimal Non-Negative Variable Weight Combination Model for Satellite Clock Bias Prediction

We consider the shortcomings of single satellite clock error prediction model.In this paper, based on three kinds of single model, i.e., the quadratic polynomial, the gray GM (1, 1) and the ARIMA models, the optimal non-negative variable weight combination forecasting model is proposed. Comparison with the single model and the classic weight combination model, shows that the RMS value of the optimal non-negative variable weight combination model prediction residual is smallest and its accuracy is higher. Moreover, it can give different weights according to the advantages and disadvantages of each model and sum up the advantages of a variety of single models in a certain degree and reduce the forecast risk. Furthermore，it can also improve the reliability of the model forecast.