Distance entropy based decision-making information fusion method

Experimental analysis show that the proposed method can solve problems of the hugeness of knowledge base and improve the objectivity and scientificity of fusion results in decision-making information fusion.

Abstract

With analysis of the features of decision-making information fusion and actual emergency decision 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 knowledge 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 hugeness of knowledge base and improve the objectivity and scientificity of fusion results in decision-making information fusion.