基于距离熵的应急决策层信息融合方法

Distance entropy based decision-making information fusion method

通过分析决策层信息融合和应急决策的特点,并考虑到应急决策对客观性、科学性的要求,提出了基于距离熵的应急决策层信息融合方法.首先基于知识元模型进行融合集的获取,并实例化知识元形成信息单元,为融合提供基础信息对象;然后在传统熵权法的基础上,添加对信息间欧式距离的测度,提出"距离熵"的概念,并据此实现局部融合权重和全局融合权重的获取,利用线性加权分别计算局部融合结果和全局融合结果.最后,通过算例验证了方法的优越性和在应急领域的适用性.同其他方法相比,本文提出的方法能有效解决决策层信息融合中融合知识库巨量性和融合结果的客观性、科学性不足等问题.

With analysis of the features of decision-making information fusion and actual emergency deci- sion making, this paper presents a decision-making information fusion method based on distance entropy according to the demand for objectivity and scientificity. Firstly, the fusion set is acquired and stored based on knowledge unit model. Secondly, the information units are formed through instantiating knowl- edge units, which can provide information support for the fusion. Afterwards, the concept of distance entropy is proposed with an element of distance added into the traditional entropy weight method. Thus, we can obtain both local and global fusion weight, finally to gain the global fusion results using the way of linear weighting. Furthermore, the application value and effectiveness of this method are illustrated by empirical analysis. Experimental analysis show that the proposed method can solve problems of the huge- ness of knowledge base and improve the objectivity and scientificity of fusion results in decision-making information fusion.