For a multi-attribute decision making (MADM) problem, the information of alternatives under different attributes is given in the form of intuitionistic fuzzy number(IFN). Intuitionistic fuzzy set (IFS) plays an important role in dealing with un-certain and incomplete information. The similarity measure of intuitionistic fuzzy sets (IFSs) has always been a research hotspot. A new similarity measure of IFSs based on the projection technology and cosine similarity measure, which con-siders the direction and length of IFSs at the same time, is first proposed in this paper. The objective of the presented pa-per is to develop a MADM method and medical diagnosis method under IFS using the projection technology and cosine similarity measure. Some examples are used to illustrate the comparison results of the proposed algorithm and some exist-ing methods. The comparison result shows that the proposed algorithm is effective and can identify the optimal scheme accurately. In medical diagnosis area, it can be used to quickly diagnose disease. The proposed method enriches the exist-ing similarity measure methods and it can be applied to not only IFSs, but also other interval-valued intuitionistic fuzzy sets(IVIFSs) as well.

翻译：针对多属性决策问题，各属性下备选方案的信息以直觉模糊数形式给出。直觉模糊集在处理不确定与不完整信息方面具有重要作用，其相似度度量始终是研究热点。本文首次提出一种基于投影技术与余弦相似度的新型直觉模糊集相似度度量方法，该方法同时考虑直觉模糊集的方向与长度。本文旨在利用投影技术与余弦相似度，构建直觉模糊环境下的多属性决策方法与医学诊断方法。通过实例对比所提算法与现有方法的计算结果，结果表明所提算法有效且能准确识别最优方案。在医学诊断领域，该方法可快速诊断疾病。本文方法丰富了现有相似度度量方法，不仅适用于直觉模糊集，还可推广至区间值直觉模糊集。