Affiliations: [a] Department of Mathematics, Kinnaird College for Women, Lahore, Pakistan
| [b] Department of Mathematics, University of the Punjab, Lahore, Pakistan
| [c] Basic Sciences Department, Preparatory Year Deanship, King Faisal University, Al-Ahsa 31982, Saudi Arabia
| [d] Department of Mathematics, Faculty of Basic andApplied Sciences, Air University, PAF Complex E-9, Islamabad, Pakistan
Correspondence:
[*]
Corresponding author. Ashraf Al-Quran, Basic Sciences Department, Preparatory Year Deanship, King Faisal University, Al-Ahsa 31982, Saudi Arabia. E-mail: [email protected].
Abstract: This research work proposes a novel approach for multi stage decision analysis (MSDA) using innovative concepts of cubic intuitionistic fuzzy set (CIFS) theory. The paper introduces CIF-technique for order preference by similarity to ideal solution (TOPSIS) as a robust method for MSDA problems, particularly for the diagnosis of epilepsy disorders. To achieve this goal, new similarity measures (SMs) are developed for CIFS, including the Cosine angle between two vectors, a new distance measure, and the Cosine function, presented as three different types of Cosine similarity measures. The proposed CIF-TOPSIS approach is found to be suitable for precise value performance ratings and is expected to be a viable approach for case studies in the diagnosis of epilepsy disorders. The efficiency and reliability of the proposed MSDA methods is efficiently carried through numerical examples and comparative analysis.
