TY - JOUR T1 - Subsethood measure for picture fuzzy sets and its applications on multicriteria decision making TT - Görüntü bulanık kümelerde altkümelik ve çok kriterli karar vermeye uygulanması AU - Köseoğlu, Ali PY - 2022 DA - April Y2 - 2022 DO - 10.17714/gumusfenbil.974420 JF - Gümüşhane Üniversitesi Fen Bilimleri Dergisi PB - Gumushane University WT - DergiPark SN - 2146-538X SP - 385 EP - 394 VL - 12 IS - 2 LA - en AB - Picture fuzzy set is a direct generalization of intuitionistic fuzzy set and is therefore more capable of dealing with uncertainty while working on real life problems. The concept of inclusion is a subject that is frequently studied in family of fuzzy sets and has many applications in real life problems. Therefore, in this work, the measuring degree of inclusion between picture fuzzy sets is introduced. For this purpose, firstly axioms for subsethood measure are given and then a subsethood measure based on a distance measure for picture fuzzy sets is proposed. Then, a numerical example is provided to illustrate the applicability and usefulness of the presented measure. Finally, results are compared with the existing methods and aggregation operator to show validity of subsethood measure for PFS. KW - MCDM KW - Picture fuzzy sets KW - Subsethood measure N2 - Görüntü bulanık küme, sezgisel bulanık kümenin doğrudan bir genellemesidir ve bu nedenle gerçek hayat problemleri üzerinde çalışırken belirsizlikle başa çıkma konusunda daha yeteneklidir. Kapsama kavramı, bulanık kümeler ailesinde sıklıkla çalışılan ve gerçek hayat problemlerinde birçok uygulaması olan bir konudur. Bu nedenle, bu çalışmada, görüntü bulanık kümeleri arasındaki kapsama derecesinin ölçülmesi tanıtılmıştır. Bu amaçla, önce altkümelik ölçüsü için aksiyomlar verilmiş, ardından görüntü bulanık kümeleri için uzaklık ölçüsüne dayalı bir altküme ölçüsü önerilmiştir. Sonra, verilen ölçünün uygulanabilirliğini ve kullanışlılığını göstermek için sayısal bir örnek verilmiştir. Son olarak, sonuçlar PFS için altkümelik ölçüsünün geçerliliğini göstermek için mevcut yöntemler ve ortalama operatörleri ile karşılaştırılmıştır. CR - Atanassov, K. T. (1986). Intuitionistic fuzzy sets. Fuzzy Sets and Systems, 20(1), 87–96. CR - Cornelis, C., & Kerre, E. (2003). Inclusion measures in intuitionistic fuzzy set theory. Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science), 2711, 345–356. https://doi.org/10.1007/978-3-540-45062-7_28 CR - Cornelis, C., Van der Donck, C., & Kerre, E. (2003). Sinha-Dougherty approach to the fuzzification of set inclusion revisited. Fuzzy Sets and Systems, 134(2), 283–295. https://doi.org/10.1016/S0165-0114(02)00225-7 CR - Cường, B. C. (2015). Picture fuzzy sets. Journal of Computer Science and Cybernetics, 30(4), 409–420. https://doi.org/10.15625/1813-9663/30/4/5032 CR - Cuong, B. C., & Kreinovich, V. (2014). 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