用于异质信息的信任区间交互式多属性识别方法

为了解决混合类型数据与专家知识等异质信息的融合决策问题，该文提出了基于信任区间的交互式多属性识别(BI-TODIM)方法。完善了混合类型数据的距离测度，根据信任区间的构建定理和灰关联方法构建了未知目标混合类型数据的信任区间，阐明了信任区间与直觉模糊数之间的等价关系，创建了混合类型数据和专家知识的识别决策模型，实现了特征层信息和决策层信息的统一表达；分析了基于信度函数的逼近理想解(BF-TOPSIS)方法的反转现象及算法的复杂度，定义了区间数的序关系，提出了BI-TODIM识别决策方法，及基于直觉模糊熵的未知权重计算方法。结合算例和目标识别案例，验证了该文方法在解决排序反转和异质信息融合方面的有效性，突出了该方法时间复杂度低、稳定性好、识别准确度高的优点。

A BI-TODIM Approach Used for Heterogeneous Information Fusion

A the Interative Multi-criteria Decision making based on Belief Interval (BI-TODIM) approach is proposed to solve the fusion decision problem of heterogeneous information with mixed type data and expert knowledge. According to the construction theorem of trust interval and grey relation method, the trust interval of mixed type data of unknown target is constructed. The equivalence relationship between trust interval and intuitionistic fuzzy number is clarified. The recognition decision model of mixed type data and expert knowledge is established. The unified expression of feature layer information and decision layer information is realized. The shortcomings of the Technique for Order Preference by Similarity to Ideal Solution based on Belief Function (BF-TOPSIS) method are analyzed such as the inversion phenomenon and the complexity. To solve this problem, the order relation of interval numbers is defined, the BI-TODIM recognition decision method and the method of calculating unknown weight based on intuitionistic fuzzy entropy are proposed. The effectiveness of the proposed method in resolving ranking inversion and heterogeneous information fusion is verified by an example and a target identification case, which underlines low time complexity, good stability and high recognition accuracy.