一种基于多准则的模糊信息融合算法决策

A Decision-making Method of Fuzzy Information Fusion Based on Multi-Criteria

信息融合的目标是结合异构信息以获取复合可对比模式的替代解决方案,因此提出一种基于多准则的模糊信息融合算法决策.该算法结合了计算智能和多准则决策领域的理论概念,首先采用归一化基本模式对归属函数进行标准化操作;其次选择有效数据信息函数值将其组合成聚合函数,然后根据聚合函数建立多准则方式来处理异构信息,最终获得每个候选替代方案的单一评价模式.实验结果表明,基于多准则的模糊信息融合算法能够处理和表示输入数据中涉及的不精确和不确定性,相比于基于模糊规则方法更具适应性.

The main goal of information fusion is to combine heterogeneous information to obtain an alternative solution for composite comparable mode.A decision-making method of fuzzy information fusion based on multi-criteria(FIFB-MC)is proposed.The basic theoretical concepts in the field of computational intelligence and multi-criteria decision-making are combined in the algorithm.Firstly,the normalized basic mode is used to standardize the attribution function.Secondly,the effective data information function value is selected to be combined into an aggregate function,and then the aggregation function is established.The standard approach to deal with heterogeneous information ultimately leads to a single evaluation model for each candidate alternative.Experimental results show that the fuzzy information fusion algorithm based on multi-criteria can process and represent the inaccuracies and uncertainties involved in the input data,and is more adaptive than the fuzzy rule-based method.