摘要
本文根据预报量与预报因子关系的实际情况,提出了预报因子的四种类型,并且利用最优化方法原理选取最优的预报因子,同时还利用强迫引进重要因子的办法选取最优预报方程。从实例计算证明,最优预报因子基本上是非线性的,所以用逐步回归或逐步判别方法建立的预报方程也是非线性的,并且还证明,非线性预报方程比线性预报方程效果有明显的提高。本文最后还指出,此种非线性预报方法可推广到各个领域有关多元分析的定量和定性预报工作中去。
In this paper, four types of predictors were proposed from the actual situation of relationship between predictand and predictors, then the optimal predictors were selected using the principles of optimization method, at the same time the optimal prediction equation was selected based on the method which was used to the forcing introduction of some important predictors. The computing results from two examples show that the optimal predictors were mainly nonlinear, so that the prediction equations builded from stepwise regression or step-wise discrimination method were also nonlinear. The authors bear out that the prediction acuracy of the nonlinear equation is better than the linear one. Finally, the authors also indicate this nonliear prediction techniques might extend to various aspects relating to the quantitative and qualitative forecasting works on multivariate analysis.
出处
《气象学报》
CSCD
北大核心
1989年第1期52-60,共9页
Acta Meteorologica Sinica
