A new method for similarity measures for pattern recognition |
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Authors: | Peter CP Yen KuoChin Fan Henry CJ Chao |
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Institution: | 1. Department of Computer Science and Information Engineering, National Central University, Taiwan;2. Department of Traffic Science, Central Police University, Taiwan |
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Abstract: | This paper points out three questionable areas in the realm of similarity measures and then provides a new method that will rectify the problem. The purpose of this paper is fourfold. First, we will propose a scenario where the three similarity measures proposed by Hung and Yang (2004) 1] are helpless in aiding a decision maker in deciding pattern recognition problem. Second, we will present our method for solving the dilemma. Third, we will show that our proposed similarity measures satisfy the axioms for well defined similarity measures. Fourth, we will prove that our method could solve pattern recognition problems. Our findings will help researchers handle similarity problems under intuitionistic fuzzy sets environment. |
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Keywords: | Intuitionistic fuzzy sets Similarity measures Pattern recognition |
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