چکیده مقاله
Distance and similarity measures are considered useful tools in a variety of scientific fields such as decision making, pattern recognition, clustering analysis, medical diagnosis, etc In this paper, we review the existing distance and similarity measures between hesitant fuzzy sets HFSs and show that in some cases they are not logical or efficient So, we propose some improved distance and similarity measures for HFSs, considering the deviation degree as a hesitancy index for these sets Comparing our novel measures with some existing distance measures shows that our proposed measures are reasonable and valid
کلیدواژهها
نویسندگان
M Najafi
Department of Mathematics, Velayat University;
A. Khosravi Tanak
Department of Statistics, Velayat University
شیوه ارجاع
Najafi, M and Khosravi Tanak, A.,1402,A novel distance and similarity measures on hesitant fuzzy sets with applications in pattern recognition,5th International Conference on Software Computing,Rudsar
ارائهشده در
مجموعه مقالات پنجمین کنفرانس بین المللی محاسبات نرم16 اسفند 1402 · رودسر