A novel complex Fermatean fuzzy formalism with improved score function and aggregation operators

Abstract In the era of intelligent systems and data-driven technologies, making precise and reliable decisions under uncertainty has become increasingly vital. The primary aim of this study is to tackle decision making (DM) issues by developing the technique of aggregation operators (AOs) within a complex Fermatean fuzzy (CFF) environment. A novel score function is defined to resolve the shortcomings of the existing score function for complex Fermatean fuzzy numbers (CFFNs). We introduce two novel ordered weighted aggregation operators: the complex Fermatean fuzzy ordered weighted averaging (CFFOWA) operator and the complex Fermatean fuzzy ordered weighted geometric (CFFOWG) operator. Furthermore, the study explores many important features of the proposed operators. The updated score function and proposed operators (CFFOWA and CFFOWG) are successfully employed to select the most optimal signal processing and communication system for better traffic control. Finally, a comparative analysis is performed to illustrate the reliability and efficacy of the proposed methods relative to existing methodologies. The study contributes to the field of assessment and decision-making by offering innovative and efficient tools and methodologies.