Analysis of Renewable Energies Based on Circular Bipolar Complex Intuitionistic Fuzzy Linguistic Information with Frank Power Aggregation Operators and MABAC Model

Intuitionistic fuzzy sets and bipolar fuzzy sets are two different ideas, used for the assessment of opinions because the intuitionistic fuzzy sets contain the membership function and non-membership function, but the bipolar fuzzy set describes opinions under two oppositional directions with the positive membership function and negative membership function. This paper develops the circular bipolar complex intuitionistic fuzzy linguistic (Cir-BCIFL) set theory, which is an extension of the numerous existing models, such as fuzzy sets, intuitionistic fuzzy sets, bipolar fuzzy sets, linguistic sets, complex fuzzy sets, and circular intuitionistic fuzzy sets to cope with vague and complex information. In a decision-making scenario, Cir-BCIFL set theory is considered a massive prominent and efficient tool than other existing techniques. Therefore, for the construction of the power aggregation operators, the operational laws based on algebraic and Frank norms for the Cir-BCIFL set are proposed. In this paper, we also derive the theory of Cir-BCIFL Frank power averaging operator, Cir-BCIFL Frank power weighted averaging operator, Cir-BCIFL Frank power geometric operator, and Cir-BCIFL Frank power weighted geometric operator with their basic properties, such as idempotency, monotonicity, and boundedness. Then a multi-attribute border approximation area comparison (MABAC) approach is proposed based on the developed theory. Renewable energy is the form of energy, which is formed or produced from natural and genuine resources that are continuously inexhaustible or replenished. This application goals to assess renewable energy in the European Union to evaluate the most prominent types for their usage in the best and worst conditions. Thus, to deliberate the rationality and efficiency of the designed model, we explain and discuss how to solve numerical problems related to renewable energy for choosing the best way of industrialization with the help of a multi-attribute decision-making model. Next, we indicate how the contribution of the parameters in our designed technique affects the decision-making results. Finally, to exhibit the worth of the initiated theory, the obtained results are compared with the existing techniques.