An algorithmic multiple attribute decision-making method for heart problem analysis under neutrosophic hypersoft expert set with fuzzy parameterized degree-based setting

Muhammad Ihsan; Muhammad Saeed; Agaeb Mahal Alanzi; Hamiden El-Wahed Khalifa

doi:10.7717/peerj-cs.1607

An algorithmic multiple attribute decision-making method for heart problem analysis under neutrosophic hypersoft expert set with fuzzy parameterized degree-based setting

PeerJ Comput Sci. 2023 Dec 4:9:e1607. doi: 10.7717/peerj-cs.1607. eCollection 2023.

Authors

Muhammad Ihsan¹, Muhammad Saeed¹, Agaeb Mahal Alanzi², Hamiden El-Wahed Khalifa^{2

3}

Affiliations

¹ Department of Mathematics, University of Management & Technology, Lahore, Pakistan.
² Department of Mathematics, College of Science and Arts, Qassim University, Al-Badaya, Saudi Arabia.
³ Department of Operations and Management Research, Faculty of Graduate Studies for Statistical Research, Cairo University, Giza, Egypt.

Abstract

A fuzzy parameterized neutrosophic hypersoft expert set (FpNHse-set) is one of the family members of fuzzy parameterized structures and a valuable extension of the neutrosophic soft expert set as well as the neutrosophic hypersoft set. This structure involves a multi-argument approximate function that has the ability to change the sub-characteristic pairs in the form of power set of universe. The main function of this structure is the classification of each character into sub-characteristic valued sets. Due to this prominent property, this mathematical structure is useful for uncertainties and also helps make the decision-making process more adaptable and dependable. By using the algebraic and basic ideas of the FpNHse-sets, a useful strategy, especially for medical diagnosis, known as Sanchez's method has been used in this study. To see a reformed process for the medical diagnosis of heart disease, a useful combination of FpNHse-set and a modified Sanchez's method has been made in this context. By using the real data from the Cleveland data set for heart disease, the implementation of the reform process has been made to see its veracity. Finally, a clear comparison of the used study with its existing studies has been made for the purpose of benefits.

Keywords: Decision-making; Fuzzy set; Fuzzy soft expert set; Hypersoft expert set; Optimization algorithm.

Grants and funding

This work was supported by the Deanship of Scientific Research, Qassim University. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.