Impact of AI Techniques in Electrical Engineering With Spherical Fuzzy Soft Geometric Aggregation Operators

All modifications to regular fuzzy sets with three-dimensional membership functions are intended to provide a more detailed definition of decision-makers and experts’ opinions. The Spherical Fuzzy Soft Set (SFSS) is the new extension of the Picture Fuzzy Soft Set (PFSS) that can cover more advanced information than PFSS. Moreover, human opinion can never be restricted to two-dimensional membership functions like yes or no, but it can be yes, abstain, no, and refusal. It means that all notions like Intuitionistic Fuzzy Soft Sets (IFSS) and Pythagorean Fuzzy Soft Sets (PyFSS) lack the property of considering three-dimensional membership functions. So, the SFSS is a more general apparatus and free from all those complexities faced by IFSS and PyFSS. The major contribution of this study is the definition of the basic operational laws for SFSSs. Aggregation Operators (AOs) are basic mathematical tools to aggregate the overall information into a single value. Consequently, we aim to introduce some new SFS geometric AOs. Additionally, the fundamental characteristics of these well-established operators are thoroughly examined and an algorithm is introduced along with numerical examples to deal with Multi-criteria Decision Making (MCDM) problems that show the advantages of the established method. In the end, a comparative analysis is carried out to reveal the superiority and authenticity of the introduced method.