Topological Data Analysis with Cubic Hesitant Fuzzy TOPSIS Approach

A hesitant fuzzy set (HFS) and a cubic (CS) are two independent approaches to deal with hesitancy vagueness simultaneously. An HFS assigns an essential grade each object in the universe, whereas CS deals uncertain information terms of sets as well interval-valued sets. (CHFS) is new computational intelligence approach that combines HFS. The primary objective this paper define topological structure CHFSs under P(R)-order develop data analysis technique. For these objectives, we propose concept “cubic topology (CHF topology)”, which based on both P(R)-order. idea CHF points gives rise study several properties topology, such closure, exterior, interior, frontier, etc. We also notion subspace base related results. proposed algorithms for extended TOPSIS method, respectively. symmetry optimal decision analyzed by computations algorithms. numerical illustrated discuss similar medical diagnoses. case heart failure diagnosis modified approach.