A Novel Complex Intuitionistic Fuzzy Linguistic Framework with Generalized Power-Geometric Aggregation Operators for Human–Machine Interface Analysis

A human-machine interface (HMI) is a technique of technology that enables communication and interaction between machines, robots, and humans. The major goal is to create an intuitive and effective means for humans to interact with awkward machinery or computerized systems. In this manuscript, we propose complex intuitionistic fuzzy linguistic (CIFL) sets and derive their valuable laws. Furthermore, we introduce the CIFL power geometric (CIFLPG) operator, CIFL power weighted geometric (CIFLPWG) operator, CIFL generalized power geometric (CIFLGPG) operator, and CIFL generalized power weighted geometric (CIFLGPWG) operator. Several fundamental properties are likewise established associated with these four techniques. Moreover, each procedure contains many features, but identifying which feature significantly influences the application of the human-machine interface is very complicated; for this, we describe the process of the multi-attribute decision-making (MADM) method using the derived operators for identifying the optimal feature for the human-machine interface to improve the performance of the proposed operators. Subsequently, we discuss a comparison of the proposed methods against selected existing techniques through numerical examples to show the superiority as well as flexibility of the proposed method.