Multiple-attribute decision-making for selection of medical robotic engineering based on logarithmic square root neutrosophic normal approach

Abstract

We introduce the concept of logarithmic square root neutrosophic normal interval-valued set (LO-SRNSNIVS) based on multiple attribute decision-making (MADM) problems that can be solved in our communication. The logarithmic square root neutrosophic sets (LO-SRNSSs) are new approach of the interval-valued neutrosophic sets (IVNSSs) and neutrosophic sets (NSSs). We will examine a number of aggregating operators (AOs). The LO-SRNSNIV using weighted (LO-SRNSNIVW) operators of this article. Now, we presented logarithmic square root NSNIVW averaging (LO-SRNSNIVWA), logarithmic square root NSNIVW geomentric (LO-SRNSNIVWG), logarithmic square root generalized NSNIVW averaging (LO-SRGNSNIVWA) and logarithmic square root generalized NSNIVW geometric (LO-SRGNSNIVWG). We also develop an algorithm to solve MADM problems. A real-world scenario is given with examples, as well as explanations of how Euclidean distance (ED) and Hamming distance (HD) are applied. We will explain the properties of these sets using various algebraic structures. The notion for the scoring function, accuracy function and operational laws of the LO-SRNSNIVS. In addition to their simplicity and practicality, they can help determine which option is best to pursue. Thus, the results of the described models are more understandable and closely related to integer $ \Psi $. A few proposed and existing models are also compared in order to demonstrate their validity and applicability.