Abstract
AbstractThe purpose of this paper is to develop an integrated similarity measures model based on intuitionistic fuzzy sets. This integrated model has improved two similarity measures methods: (1) Ye (Mathematical and Computer Modelling, 53, 91-97 (2011)) presented a novel cosine similarity measures method for handling pattern recognition problems based on intuitionistic fuzzy sets. However, in some cases, Ye's method can not give sufficient information to discriminate a sample between two patterns. Therefore, we provide an improved method for the similarity measure. (2) Hung et al. (Computer-Aided Design, 40, 447-454 (2008)) provided a new score function to measure the degree of suitability of each alternative. In this paper, we extend their method to modify the hesitation parameter with rate operations as a defuzzfication function for each characteristic, and then the defuzzy results as a parameter input new similarity measure method based on the Minkowski distance conception. Finally, the proposed simil...
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