Similarity measure on intuitionistic fuzzy sets
来源期刊：中南大学学报(英文版)2013年第8期
论文作者：PARK Jean-Ho HWANG Jai-Hyuk PARK Wook-Je WEI He(魏荷) LEE Sang-Hyuk
文章页码：2233 - 2238
Key words：similarity measure; multi-dimension; discrete data; relative degree; power interconnected system
Abstract: Study of fuzzy entropy and similarity measure on intuitionistic fuzzy sets (IFSs) was proposed and analyzed. Unlike fuzzy set, IFSs contain uncertainty named hesitance, which is contained in fuzzy membership function itself. Hence, designing fuzzy entropy is not easy because of many entropy definitions. By considering different fuzzy entropy definitions, fuzzy entropy on IFSs is designed and discussed. Similarity measure was also presented and its usefulness was verified to evaluate degree of similarity.
PARK Jean-Ho1, HWANG Jai-Hyuk2, PARK Wook-Je3, WEI He(魏荷)4, LEE Sang-Hyuk4
(1. Advanced Convergent Technology R&D Group, Korea Institute of Industrial Technology, Ansan 426-910, Korea;
2. School of Aerospace & Mechanical Engineering, Korea Aerospace University, Goyang-si 412-791, Korea;
3. Institute for Information and Electronics Research, Inha University, Incheon 402-751, Korea;
4. Department of Electrical and Electronic Engineering, Xi’an Jiaotong-Liverpool University,
Suzhou 215123, China)
Abstract:Study of fuzzy entropy and similarity measure on intuitionistic fuzzy sets (IFSs) was proposed and analyzed. Unlike fuzzy set, IFSs contain uncertainty named hesitance, which is contained in fuzzy membership function itself. Hence, designing fuzzy entropy is not easy because of many entropy definitions. By considering different fuzzy entropy definitions, fuzzy entropy on IFSs is designed and discussed. Similarity measure was also presented and its usefulness was verified to evaluate degree of similarity.
Key words:similarity measure; multi-dimension; discrete data; relative degree; power interconnected system
