Affiliations: [a]
Department of Mathematical Science, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, Malaysia
| [b]
Department of Mathematics, Faculity of Education for Pure Sciences, University of Anbar, Ramadi, Anbar, Iraq
| [c] Preparatory Year Deanship, King Faisal University, Hofuf, Al-Ahsa, Saudi Arabia
Correspondence:
[*]
Corresponding author. Faisal Al-Sharqi, Department of Mathematical Sciences, Faculty of Science and Technology, Universiti KebangSaan Malaysia, 43600 UKM Bangi Selangor DE, Malaysia. E-mails: ghafur@ukm.edu.my; faisal.ghazi@uoanbar.edu.iq
Abstract: Interval complex neutrosophic soft set (ICNSS) is the generalization of complex neutrosophic soft set (CNSS) as it provides an interval-based membership structure to handle the complex neutrosophic soft data. However, in the definition of the ICNSS, parameters set is a classical set, and the parameters have the same degree of importance which is considered as 1. This poses a limitation in modeling of some problems. Therefore, we introduce the concept of fuzzy parameterized interval complex neutrosophic soft set (FP-ICNSS) based on idea that each of elements of parameters set has got an importance degree. The basic theoretical operations and properties are defined and verified on FP-ICNSS. For FP-ICNSS, we conceptualize the relevant mapping and study the properties of the FP-ICNSS images and inverse images. Then, we propose a new algorithm that is applicable in the field of medical diagnosis and decision-making problems for selection right product. Moreover, an illustrative example is presented which depicts its validity for successful application to the problems involving vagueness and uncertainties. Eventually, a comparison between the proposed model and the existing methods is conducted to clarify the importance of this model.
