Some New Techniques of Computing Correlation Coefficient between q-Rung Orthopair Fuzzy Sets and their Applications in Multi-Criteria Decision-Making

Paul Augustine Ejegwa

Article Details

Some New Techniques of Computing Correlation Coefficient between q-Rung Orthopair Fuzzy Sets and their Applications in Multi-Criteria Decision-Making

Authors:

Paul Augustine Ejegwa

Publisher:

Gazi University

Main Topics:

Knowledge Representation and Reasoning | Fuzzy Computation | Planning and Decision Making | Soft Computing

Journal:

Gazi University Journal of Science Vol.38 Issue 1, pp.316-340

Document Type:

Article

Publication Date:

1/2025

Document Language:

English

Document ID (Org No.):

2001341121

pISSN:

2147-1762

Keywords:

Abstract:

 The term q-rung orthopair fuzzy set is an essential variant of fuzzy set with the capacity of tackling fuzziness and imprecision in the decision-making process. A fundamental concept in the decision-making process is the idea of correlation coefficient because of its wide applications. The process of decision-making is complex due to imprecisions, and as such the idea of correlation coefficient has been investigated under q-rung orthopair fuzzy setting. Some authors have constructed some techniques of correlation coefficient under q-rung orthopair fuzzy sets with practical applications. However, these existing techniques are defectives with several drawbacks in terms of precision and alignment with the conditions of correlation coefficient. In this work, two new techniques for estimating correlation coefficient under q-rung orthopair fuzzy sets are presented and theoretically discussed. Moreover, we apply the new techniques of correlation coefficient under q-rung orthopair fuzzy sets in disease diagnosis and employment process by using simulated q-rung orthopair fuzzy data based on multi-criteria decision-making approach and recognition principle. Some comparative analyses are provided to ascertain the benefits of the new techniques of correlation coefficient under q-rung orthopair fuzzy sets over the obtainable techniques with regard to reliability and performance rating.

 The term q-rung orthopair fuzzy set is an essential variant of fuzzy set with the capacity of tackling fuzziness and imprecision in the decision-making process. A fundamental concept in the decision-making process is the idea of correlation coefficient because of its wide applications. The process of decision-making is complex due to imprecisions, and as such the idea of correlation coefficient has been investigated under q-rung orthopair fuzzy setting. Some authors have constructed some techniques of correlation coefficient under q-rung orthopair fuzzy sets with practical applications. However, these existing techniques are defectives with several drawbacks in terms of precision and alignment with the conditions of correlation coefficient. In this work, two new techniques for estimating correlation coefficient under q-rung orthopair fuzzy sets are presented and theoretically discussed. Moreover, we apply the new techniques of correlation coefficient under q-rung orthopair fuzzy sets in disease diagnosis and employment process by using simulated q-rung orthopair fuzzy data based on multi-criteria decision-making approach and recognition principle. Some comparative analyses are provided to ascertain the benefits of the new techniques of correlation coefficient under q-rung orthopair fuzzy sets over the obtainable techniques with regard to reliability and performance rating.

 The term q-rung orthopair fuzzy set is an essential variant of fuzzy set with the capacity of tackling fuzziness and imprecision in the decision-making process. A fundamental concept in the decision-making process is the idea of correlation coefficient because of its wide applications. The process of decision-making is complex due to imprecisions, and as such the idea of correlation coefficient has been investigated under q-rung orthopair fuzzy setting. Some authors have constructed some techniques of correlation coefficient under q-rung orthopair fuzzy sets with practical applications. However, these existing techniques are defectives with several drawbacks in terms of precision and alignment with the conditions of correlation coefficient. In this work, two new techniques for estimating correlation coefficient under q-rung orthopair fuzzy sets are presented and theoretically discussed. Moreover, we apply the new techniques of correlation coefficient under q-rung orthopair fuzzy sets in disease diagnosis and employment process by using simulated q-rung orthopair fuzzy data based on multi-criteria decision-making approach and recognition principle. Some comparative analyses are provided to ascertain the benefits of the new techniques of correlation coefficient under q-rung orthopair fuzzy sets over the obtainable techniques with regard to reliability and performance rating.

 The term q-rung orthopair fuzzy set is an essential variant of fuzzy set with the capacity of tackling fuzziness and imprecision in the decision-making process. A fundamental concept in the decision-making process is the idea of correlation coefficient because of its wide applications. The process of decision-making is complex due to imprecisions, and as such the idea of correlation coefficient has been investigated under q-rung orthopair fuzzy setting. Some authors have constructed some techniques of correlation coefficient under q-rung orthopair fuzzy sets with practical applications. However, these existing techniques are defectives with several drawbacks in terms of precision and alignment with the conditions of correlation coefficient. In this work, two new techniques for estimating correlation coefficient under q-rung orthopair fuzzy sets are presented and theoretically discussed. Moreover, we apply the new techniques of correlation coefficient under q-rung orthopair fuzzy sets in disease diagnosis and employment process by using simulated q-rung orthopair fuzzy data based on multi-criteria decision-making approach and recognition principle. Some comparative analyses are provided to ascertain the benefits of the new techniques of correlation coefficient under q-rung orthopair fuzzy sets over the obtainable techniques with regard to reliability and performance rating.

Article Details

Some New Techniques of Computing Correlation Coefficient between q-Rung Orthopair Fuzzy Sets and their Applications in Multi-Criteria Decision-Making

Authors:

Paul Augustine Ejegwa

Publisher:

Gazi University

Main Topics:

Knowledge Representation and Reasoning | Fuzzy Computation | Planning and Decision Making | Soft Computing

Journal:

Gazi University Journal of Science Vol.38 Issue 1, pp.316-340

Document Type:

Article

Publication Date:

1/2025

Document Language:

English

Document ID (Org No.):

2001341121

pISSN:

2147-1762

Pythagorean fuzzy set

q-Rung orthopair fuzzy set

Disease diagnosis

Intuitionistic fuzzy set

Fermatean fuzzy set

Issues

Article Details

Some New Techniques of Computing Correlation Coefficient between q-Rung Orthopair Fuzzy Sets and their Applications in Multi-Criteria Decision-Making

Authors: Paul Augustine Ejegwa

Publisher: Gazi University

Main Topics: Knowledge Representation and Reasoning | Fuzzy Computation | Planning and Decision Making | Soft Computing

Journal: Gazi University Journal of Science Vol.38 Issue 1, pp.316-340

Document Type: Article

Publication Date: 1/2025

Document Language: English

Document ID (Org No.): 2001341121

pISSN: 2147-1762

Pythagorean fuzzy set

q-Rung orthopair fuzzy set

Disease diagnosis

Intuitionistic fuzzy set

Fermatean fuzzy set

Issues

Authors:

Paul Augustine Ejegwa

Publisher:

Gazi University

Main Topics:

Knowledge Representation and Reasoning | Fuzzy Computation | Planning and Decision Making | Soft Computing

Journal:

Gazi University Journal of Science Vol.38 Issue 1, pp.316-340

Document Type:

Article

Publication Date:

1/2025

Document Language:

English

Document ID (Org No.):

2001341121

pISSN:

2147-1762