基于层次分析法的自适应决策评价方法

为改善经典层次分析法(AHP)主观性强、权重系数固定不变的缺陷,根据被评价对象指标值矩阵所蕴含的客观信息,对经典的层次分析法进行修正,提出了一种基于层次分析法的可变权重决策评价方法。该方法能够根据被评价对象指标值的分布特征,对评价指标的权重进行动态修正,降低区分度不高的指标权重,提升区分度高的指标权重,从而提升层次分析法的客观性,并在一定程度上体现出稀缺性指标的导向作用。以合成孔径雷达图像降斑算法评价为例,验证了本文方法的有效性。

Adaptive evaluation method based on analytic hierarchy process

In order to improve the performance of classical analytic hierarchy process (AHP) which has defects of subjectivity and less quantitative component, at the same time according to the objective information which is implied by a plurality of target data matrix, the classical AHP was modified and a changeable weight evaluation method based on AHP was proposed. The conclusion is that the new method is able to adjust the weights of the evaluative parameter dynamically by analysis of the data distribution. By this way the weight of low discrimination index is reduced while the weight of high discrimination index is improved, which makes the AHP more objective, and to some extent the guiding role of the scarcity index is also reflected. The effectiveness of the new method is verified by using the example of the evaluation of the despeckling algorithm of synthetic aperture radar image.