Abstract:

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．

Key words: attribute reduction, fuzzy information system, multi-source information fusion, rough set