Determination of the most influential robot in the medical field by utilizing the bipolar complex fuzzy soft aggregation operators

Abstract

From science fiction to the hospital, robots are transforming the medical field. These robots mostly look like R2D2 from Star Wars more than humanoids, yet they are having a substantial impact on the medical field. Robots in the medical field support by releasing medical staff from repetitive chores that distract their consideration to more vital responsibilities and by dropping the danger and expenditure of medical treatment for patients. The robots can also move hazardous materials and execute accurate surgery in small spaces. Considering this influence of robots on the medical field, in this manuscript, we investigate the influence of robots on the medical field and discover which robot is more influential in the medical field. For this, the bipolar complex fuzzy soft set (BCFSS) is a substantial mathematical model that covers genuine decision-making (DM) dilemmas where the obscurity and imprecision contain a negative pole, 2nd dimension, and parameterization at one time. Moreover, in this study, we establish arithmetic and geometric aggregation operators (AOs) in the setting of BCFSS, like bipolar complex fuzzy soft-weighted arithmetic averaging (BCFSWAA) and bipolar complex fuzzy soft-weighted geometric averaging (BCFSWGA) operators. Moreover, for discovering the most influential robot, we invent a technique of DM relying on the diagnosed AOs in the environment of BCFSS, and then, we describe a numerical example (determination of the most influential robot in the medical field). To demonstrate the superiority and condescension of our work we compare it with prevailing work.