Providing decision-making approaches for the assessment and selection of cloud computing using bipolar complex fuzzy Einstein power aggregation operators

Abstract

In the last few years, cloud computing has become more popular. When someone refers to “the cloud,” which is where personal and professional documents are stored, they are moving away from more conventional software tools and apps and toward a more sophisticated use of the internet. A new technology known as “cloud computing” mainly refers to a centralized storage area made feasible by remote computers running software on the internet. Users will distribute services and resources throughout the network to enhance productivity. The selection and evaluation of cloud computing can be done by various approaches. In this manuscript, we analyze new approaches for the appraisal and selection of cloud computing. These approaches are based on the power Einstein AOs (PEAOs) which are also invented in this paper in the environment of bipolar complex fuzzy (BCF) information. Further, we do a comparative study of the devised work with several prevailing work from the literature to represent the advantages and dominance of the devised work.