CRITIC Weight Calculation Method Based on Quartiles and Improved Distance Correlation Coefficient and Its Applications.
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| Title: | CRITIC Weight Calculation Method Based on Quartiles and Improved Distance Correlation Coefficient and Its Applications. |
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| Authors: | Xie, Ailing1 906463038@qq.com, Chang, Huilong1 1209685683@qq.com, Li, Chaonan1 3066969239@qq.com, Zou, Limin2 307376216@qq.com |
| Source: | Engineering Letters. Jul2026, Vol. 34 Issue 7, p2764-2774. 11p. |
| Subjects: | Quantiles, Statistical correlation, Robust statistics, Statistical measurement, Multiple criteria decision making |
| Abstract: | In multi-criteria decision-making, the determination of weights is a critical step, as it has a direct and significant impact on the rationality and accuracy of the decision results. The traditional CRITIC method for weight calculation utilizes the standardized deviations, after dimensionless normalization, to reflect the variability among the indicators. This paper analyzes two case studies to highlight the limitations of using standardized deviations after dimensionless normalization to measure the variability among indicators, and expounds the reasons why the existing literature uses the coefficient of variation to improve the CRITIC weight calculation method. At the same time, we observed that both the coefficient of variation and the distance correlation coefficient are sensitive to outliers, leading to unstable weight calculation results and low robustness. In light of this, this paper proposes a CRITIC weight calculation method based on quartiles and improved distance correlation coefficient (QD-CRITIC). The proposed method first measures the variability among the indicators using the ratio of the interquartile range to the median. It then calculates the conflict among indicators using improved distance correlation coefficient. Furthermore, six different weight assignment methods are applied to the Iris dataset to compute the weights of the indicators, and a comparative analysis of the resulting weights is conducted. Finally, the proposed weight calculation method is applied to real-world cases in the natural gas and surface water industries. To validate the effectiveness of the proposed method, a comparative analysis is conducted with five other commonly used weight assignment methods. The results show that the weights calculated using the proposed method are consistent with the actual situation and demonstrate strong robustness. [ABSTRACT FROM AUTHOR] |
| Copyright of Engineering Letters is the property of International Association of Engineers (IAENG) and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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| Header | DbId: egs DbLabel: Engineering Source An: 195088780 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: CRITIC Weight Calculation Method Based on Quartiles and Improved Distance Correlation Coefficient and Its Applications. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Xie%2C+Ailing%22">Xie, Ailing</searchLink><relatesTo>1</relatesTo><i> 906463038@qq.com</i><br /><searchLink fieldCode="AR" term="%22Chang%2C+Huilong%22">Chang, Huilong</searchLink><relatesTo>1</relatesTo><i> 1209685683@qq.com</i><br /><searchLink fieldCode="AR" term="%22Li%2C+Chaonan%22">Li, Chaonan</searchLink><relatesTo>1</relatesTo><i> 3066969239@qq.com</i><br /><searchLink fieldCode="AR" term="%22Zou%2C+Limin%22">Zou, Limin</searchLink><relatesTo>2</relatesTo><i> 307376216@qq.com</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Engineering+Letters%22">Engineering Letters</searchLink>. Jul2026, Vol. 34 Issue 7, p2764-2774. 11p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Quantiles%22">Quantiles</searchLink><br /><searchLink fieldCode="DE" term="%22Statistical+correlation%22">Statistical correlation</searchLink><br /><searchLink fieldCode="DE" term="%22Robust+statistics%22">Robust statistics</searchLink><br /><searchLink fieldCode="DE" term="%22Statistical+measurement%22">Statistical measurement</searchLink><br /><searchLink fieldCode="DE" term="%22Multiple+criteria+decision+making%22">Multiple criteria decision making</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: In multi-criteria decision-making, the determination of weights is a critical step, as it has a direct and significant impact on the rationality and accuracy of the decision results. The traditional CRITIC method for weight calculation utilizes the standardized deviations, after dimensionless normalization, to reflect the variability among the indicators. This paper analyzes two case studies to highlight the limitations of using standardized deviations after dimensionless normalization to measure the variability among indicators, and expounds the reasons why the existing literature uses the coefficient of variation to improve the CRITIC weight calculation method. At the same time, we observed that both the coefficient of variation and the distance correlation coefficient are sensitive to outliers, leading to unstable weight calculation results and low robustness. In light of this, this paper proposes a CRITIC weight calculation method based on quartiles and improved distance correlation coefficient (QD-CRITIC). The proposed method first measures the variability among the indicators using the ratio of the interquartile range to the median. It then calculates the conflict among indicators using improved distance correlation coefficient. Furthermore, six different weight assignment methods are applied to the Iris dataset to compute the weights of the indicators, and a comparative analysis of the resulting weights is conducted. Finally, the proposed weight calculation method is applied to real-world cases in the natural gas and surface water industries. To validate the effectiveness of the proposed method, a comparative analysis is conducted with five other commonly used weight assignment methods. The results show that the weights calculated using the proposed method are consistent with the actual situation and demonstrate strong robustness. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Engineering Letters is the property of International Association of Engineers (IAENG) and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 11 StartPage: 2764 Subjects: – SubjectFull: Quantiles Type: general – SubjectFull: Statistical correlation Type: general – SubjectFull: Robust statistics Type: general – SubjectFull: Statistical measurement Type: general – SubjectFull: Multiple criteria decision making Type: general Titles: – TitleFull: CRITIC Weight Calculation Method Based on Quartiles and Improved Distance Correlation Coefficient and Its Applications. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Xie, Ailing – PersonEntity: Name: NameFull: Chang, Huilong – PersonEntity: Name: NameFull: Li, Chaonan – PersonEntity: Name: NameFull: Zou, Limin IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 07 Text: Jul2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 1816093X Numbering: – Type: volume Value: 34 – Type: issue Value: 7 Titles: – TitleFull: Engineering Letters Type: main |
| ResultId | 1 |
