人们从多个渠道得到大量的模糊信息，将这些信息进行融合以得到更加精确的 信息就变得尤为重要。文中首先利用条件熵构造了多源模糊信息系统的融合模型，此模 型通过利用新的条件熵将多个模糊信息系统最终融合成一个模糊信息表; 然后利用任意 两个模糊集合之间的贴进度来构造两个模糊关系之间的相似度，建立了 3 种模糊关系相 似度。此外，基于多源模糊信息系统融合后的模糊信息表，根据 3 种模糊关系相似度来 对融合后的模糊信息表进行属性约简，进而实现多源模糊信息系统的属性约简; 最后通 过实验验证了所分析与设计模型的正确性和有效性。结果表明，文中提出的多源模糊信 息系统的约简方法在处理模糊数据方面具有一定的价值，丰富了知识发现的理论基础。

People get a lot of fuzzy information from multiple channels，so it is very important to fuse the obtained information to get more accurate information． In this paper，a fusion model of multi-source fuzzy information system was constructed by using conditional entropy． The new conditional entropy was used to fuse multiple fuzzy information systems into a fuzzy information table． Then，the similarity between two fuzzy relations was constructed by using the paste progress between any two fuzzy sets，and three kinds of fuzzy relation similarity were established． In addition，based on the fused fuzzy information table of multi-source fuzzy information system，the attribute reduction of the fused fuzzy information table was carried out according to three kinds of fuzzy relation similarity，and then the attribute reduction of multi-source fuzzy information system was realized． Finally，the correctness and effectiveness of the proposed model was verified by experiments． The results show that the reduction method of multi-source fuzzy information system proposed in this paper has a certain value in dealing with fuzzy data and enriches the theoretical basis of knowledge discovery．