Open Access

ARTICLE

Interval-Valued Neutrosophic Soft Expert Set from Real Space to Complex Space

Faisal Al-Sharqi^1,2, Abd Ghafur Ahmad^1,*, Ashraf Al-Quran³

1 Department of Mathematical Sciences, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, Bangi, Selangor, 43600, Malaysia
2 Department of Mathematics, Faculty of Education for Pure Sciences, University of Anbar, Ramadi, 55431, Iraq
3 Preparatory Year Deanship, King Faisal University, Hofuf, Al-Ahsa, 31982, Saudi Arabia

* Corresponding Author: Abd Ghafur Ahmad. Email:

(This article belongs to the Special Issue: Extension, Modeling and Applications of Fuzzy Set Theory in Engineering and Science)

Computer Modeling in Engineering & Sciences 2022, 132(1), 267-293. https://doi.org/10.32604/cmes.2022.019684

Received 08 October 2021; Accepted 17 December 2021; Issue published 02 June 2022

Abstract

A fuzzy system is a novel computing technique that accesses uncertain information by fuzzy representation. In the decision-making process, fuzzy system and soft computing are effective tools that are tolerant to imprecision, uncertainty, and partial truths. Evolutionary fuzzy systems have been developed with the appearance of interval fuzzy, dual fuzzy, hesitant fuzzy, neutrosophic, plithogenic representations, etc. Moreover, by capturing compound features and convey multi-dimensional data, complex numbers are utilized to generalize fuzzy and neutrosophic fuzzy sets. In this paper, a representation of neutrosophic soft expert systems based on the real and complex numbers in the interval form is proposed. The interval-valued neutrosophic soft expert set (I-VNSES) is defined, and the interval-valued complex neutrosophic soft expert set (I-VCNSES) is formally generalized from the concept of I-VNSES. For both I-VNSES and I-VCNSES, we introduce the relevant basic theoretical operations and study their properties. Based on these new concepts, a generalized algorithm is proposed and applied to handle the imbedded indeterminacy in the two-dimensional interval data. The proposed algorithm is tested on the economic factors that affected the Malaysian economy in 2020 to see which ones are the most influential. Eventually, a comparison of three current approaches is used to back up this study.

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Keywords

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