Evaluation of Data Analysis Software Using T-Spherical Fuzzy Einstein Aggregation Operators With Unknown Weights

The multi-attribute group decision-making (MAGDM) technique is a potent approach used to evaluate an appropriate optimal option under the system of various characteristics or attributes information. The aggregation operators (AOs) play a significant role in the aggregation process and fuse a large amount of uncertain information into a single set. In this article, dominant terminologies of t-spherical fuzzy sets apply to handle vague and ambiguous information related to human opinion. Some flexible operations of Einstein operations are also modified in the light of t-spherical fuzzy information. The power operators characterized relationships among various types of preference information. Keeping in mind the significance of discussed terminologies, we developed some Einstein mathematical approaches, including T-SF Einstein power-weighted average (T-SFEPWA) and T-SF Einstein power-weighted geometric (T-SFEPWG) operators. Some desirable characteristics and special cases are also demonstrated to reveal the reliability of developed approaches. An algorithm for the MAGDM problem is also established to resolve different real-life situations. To show the consistency and effectiveness of the proposed approaches, the author illustrates a numerical example to choose an appropriate data analysis tool under the system of T-SF information. Additionally, a comprehensive comparison method verifies the validity and feasibility of diagnosed mathematical approaches with existing AOs in the literature.