| Summary: | 碩士 === 國立新竹教育大學 === 數學教育學系碩士班 === 95 === A Similarity measure between intuitionistic fuzzy sets is a very important and practical in a lot of fields. Many different similarity measures between intuitionistic fuzzy sets have already been derived and calculated in some literature, and apply similarity measures on the issue that pattern recognition, machine learning, group decision making and market prediction, etc. In this paper is mainly used by Perlibakas(2004) originated the sixteen distance formulas. Using five formulas of them as the distance measures of intuitionistic fuzzy sets, and than create seven new similarity measures between intuitionistic fuzzy sets. Finally, we are applying the question of group decision making, and comparing the methods of group decision making in the other scholars.
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