TY  - EJOU
AU  - Palanikumar, Murugan 
AU  - Kausar, Nasreen 
AU  - Pamucar, Dragan 
AU  - Kadry, Seifedine 
AU  - Kim, Chomyong 
AU  - Nam, Yunyoung 

TI  - Novelty of Different Distance Approach for Multi-Criteria Decision-Making Challenges Using <i>q</i>-Rung Vague Sets
T2  - Computer Modeling in Engineering \& Sciences

PY  - 2024
VL  - 139
IS  - 3
SN  - 1526-1506

AB  - In this article, multiple attribute decision-making problems are solved using the vague normal set (VNS). It is possible to generalize the vague set (VS) and <i>q</i>-rung fuzzy set (FS) into the <i>q</i>-rung vague set (VS). A log <i>q</i>-rung normal vague weighted averaging (log <i>q</i>-rung NVWA), a log <i>q</i>-rung normal vague weighted geometric (log <i>q</i>-rung NVWG), a log generalized <i>q</i>-rung normal vague weighted averaging (log G<i>q</i>-rung NVWA), and a log generalized <i>q</i>-rung normal vague weighted geometric (log G<i>q</i>-rung NVWG) operator are discussed in this article. A description is provided of the scoring function, accuracy function and operational laws of the log <i>q</i>-rung VS. The algorithms underlying these functions are also described. A numerical example is provided to extend the Euclidean distance and the Humming distance. Additionally, idempotency, boundedness, commutativity, and monotonicity of the log <i>q</i>-rung VS are examined as they facilitate recognizing the optimal alternative more quickly and help clarify conceptualization. We chose five anemia patients with four types of symptoms including seizures, emotional shock or hysteria, brain cause, and high fever, who had either retrograde amnesia, anterograde amnesia, transient global amnesia, post-traumatic amnesia, or infantile amnesia. Natural numbers <i>q</i> are used to express the results of the models. To demonstrate the effectiveness and accuracy of the models we are investigating, we compare several existing models with those that have been developed.
KW  - Vague set; aggregating operators; euclidean distance; hamming distance; decision making

DO  - 10.32604/cmes.2024.031439