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

Tehreem; Ali Akgül; Muhammad Riaz; Kinza Ayaz; Haider Ali

doi:10.59543/5q502x93

Authors

Tehreem Department of Mathematics, Faculty of Basic and Applied Sciences, Air University PAF Complex E-9, Islamabad, 44000, Pakistan. https://orcid.org/0000-0002-5358-1553 Author
Ali Akgül Department of Electronics and Communication Engineering, Saveetha School of Engineering, SIMATS, Chennai, Tamil Nadu, India; Faculty of Science, Department of Computer Sciences, Karadeniz Technical University, Trabzon, Türkiye; Siirt University, Art and Science Faculty, Department of Mathematics, 56100 Siirt, Türkiye; Department of Computer Engineering, Biruni University, 34010 Topkapı, Istanbul, Türkiye; Near East University, Mathematics Research Center, Department of Mathematics, Near East Boulevard, PC: 99138, Nicosia/Mersin 10, Türkiye; Applied Science Research Center, Applied Science Private University, Amman, Jordan. https://orcid.org/0000-0001-9832-1424 Author
Muhammad Riaz Institute of Mathematics, University of the Punjab, Quaid-e-Azam Campus, Lahore-54590, Pakistan. https://orcid.org/0000-0001-8115-9168 Author
Kinza Ayaz Department of Physics, Faculty of Basic and Applied Sciences, Air University, PAF Complex E-9, Islamabad, 44000, Pakistan. https://orcid.org/0009-0007-9757-2513 Author
Haider Ali Department of Mathematics, COMSATS University Islamabad, Vehari Campus, Pakistan. https://orcid.org/0000-0002-2551-9621 Author

DOI:

https://doi.org/10.59543/5q502x93

Keywords:

Human-machine interface; complex intuitionistic linguistic sets; generalized power-geometric aggregation operators; decision-making approach

Abstract

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.