Author
Tzu-Chun Lan
Bio: Tzu-Chun Lan is an academic researcher from National Taiwan University of Science and Technology. The author has contributed to research in topics: Fuzzy measure theory & Fuzzy classification. The author has an hindex of 4, co-authored 4 publications receiving 261 citations.
Papers
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TL;DR: The experimental results show that the proposed similarity measure between intuitionistic fuzzy sets can overcome the drawbacks of the existing similarity measures.
165 citations
TL;DR: The proposed MCDM method based on the TOPSIS method and similarity measures between intuitionistic fuzzy values (IFVs) can overcome the drawbacks of Joshi and Kumar's method, Wang and Wei's method and Wu and Chen's method.
160 citations
01 Jul 2016
TL;DR: A novel multicriteria decision making (MCDM) method using the TOPSIS method and similarity measures between intuitionistic fuzzy values that can overcome the drawbacks of the existing MCDM methods in intuitionist fuzzy environments.
Abstract: This paper proposes a novel multicriteria decision making (MCDM) method using the TOPSIS method and similarity measures between intuitionistic fuzzy values. First, it calculates the degree of indeterminacy (DOI) of each evaluating intuitionistic fuzzy value (IFV) given by the decision maker. Then, it calculates the DOI of the relative positive ideal value (RPIV) and the relative negative ideal value (RNIV) for each criterion, respectively. Then, it calculates the positive similarity degrees and the negative similarity degrees. Finally, it calculates the weighted positive score and the weighted negative score of each alternative, respectively, to get the relative degree of closeness of each alternative. The advantage of the proposed MCDM method is that it can overcome the drawbacks of the existing MCDM methods for MCDM in intuitionistic fuzzy environments.
9 citations
01 Oct 2015
TL;DR: A new similarity measure between intuitionistic fuzzy sets (IFSs) for pattern recognition based on the centroid points of transformed right-angled triangular fuzzy numbers to deal with pattern recognition problems is proposed.
Abstract: This paper proposes a new similarity measure between intuitionistic fuzzy sets (IFSs) for pattern recognition based on the centroid points of transformed right-angled triangular fuzzy numbers to deal with pattern recognition problems. The proposed similarity measure between IFSs outperforms the existing similarity measures for dealing with the pattern recognition problems.
6 citations
Cited by
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TL;DR: The proposed MADM method can overcome the drawbacks of the existing MADM methods for MADM in intuitionistic fuzzy environments and the proposed modified VIKOR method.
177 citations
TL;DR: A new distance measure between IFSs is proposed and proves some of its useful properties and an extended intuitionistic fuzzy TOPSIS approach is developed to handle the MCDM problems.
175 citations
TL;DR: In this article, the authors proposed an innovative MAGDM (multiattribute group decision making) process based on weighted averaging neutral aggregation operators (AOs) to aggregate the q-ROF erudition.
170 citations
TL;DR: This study maps the research landscape to provide a clear taxonomy of fuzzy multi-criteria decision making (FMCDM) and searches for articles related to technique for order of preference by similarity to ideal solution (TOPSIS), development, development and fuzzy sets in four primary databases.
168 citations
TL;DR: The experimental results show that the proposed similarity measure between intuitionistic fuzzy sets can overcome the drawbacks of the existing similarity measures.
165 citations