Linear Diophantine Fuzzy Clustering Algorithm Based on Correlation Coefficient and Analysis on Logistic Efficiency of Food Products
The significance of clustering algorithms lies in their ability to distinguish problems and devise customized solutions. In the broader context of clustering, fuzzy clustering is one of the crucial aspects. In response to the real-world clustering problems, this research suggests a new fuzzy cluster...
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| Format: | Article |
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IEEE
2024-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/10456891/ |
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| author | Jeevitha Kannan Vimala Jayakumar Muhammad Saeed Tmader Alballa Hamiden Abd El-Wahed Khalifa Heba Ghareeb Gomaa |
| author_facet | Jeevitha Kannan Vimala Jayakumar Muhammad Saeed Tmader Alballa Hamiden Abd El-Wahed Khalifa Heba Ghareeb Gomaa |
| author_sort | Jeevitha Kannan |
| collection | DOAJ |
| description | The significance of clustering algorithms lies in their ability to distinguish problems and devise customized solutions. In the broader context of clustering, fuzzy clustering is one of the crucial aspects. In response to the real-world clustering problems, this research suggests a new fuzzy cluster scheme of data under the linear diophantine fuzzy set(LDFS) framework. More precisely, LDF clustering is initiated with the aid of the correlation coefficient(<inline-formula> <tex-math notation="LaTeX">$\mathcal {CC}$ </tex-math></inline-formula>) and weighted correlation coefficient(<inline-formula> <tex-math notation="LaTeX">$\mathcal {WCC}$ </tex-math></inline-formula>) for LDFS. Due to their ability to quantify the degree of similarity between two elements, <inline-formula> <tex-math notation="LaTeX">$\mathcal {CC}$ </tex-math></inline-formula> are valuable in clustering problems. The LDF- clustering algorithm comprises a well-integrated algorithm for managing uncertainty and <inline-formula> <tex-math notation="LaTeX">$\mathcal {CC}$ </tex-math></inline-formula> among LDFS. Also, our approach to LDF clustering is compared to existing fuzzy clustering studies to assess its effectiveness. Since LDFS broadens the score space, the experimental evaluation of our proposed scheme enables Decision makers(DM) to freely select their score values. The theme of this study is to impart the commencement of LDF-clustering analysis and attempt to apply <inline-formula> <tex-math notation="LaTeX">$\mathcal {CC}$ </tex-math></inline-formula> to the clustering problem. An interpretative example provides the analysis of the logistic efficiency of food products by employing an LDF-clustering algorithm. |
| first_indexed | 2024-04-24T18:54:13Z |
| format | Article |
| id | doaj.art-a9495f07fa254091a4d413cd9b207468 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-04-24T18:54:13Z |
| publishDate | 2024-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-a9495f07fa254091a4d413cd9b2074682024-03-26T17:46:49ZengIEEEIEEE Access2169-35362024-01-0112348893490210.1109/ACCESS.2024.337198610456891Linear Diophantine Fuzzy Clustering Algorithm Based on Correlation Coefficient and Analysis on Logistic Efficiency of Food ProductsJeevitha Kannan0https://orcid.org/0000-0001-7846-9173Vimala Jayakumar1https://orcid.org/0000-0003-3138-9365Muhammad Saeed2https://orcid.org/0000-0002-7284-6908Tmader Alballa3https://orcid.org/0000-0002-0776-2652Hamiden Abd El-Wahed Khalifa4Heba Ghareeb Gomaa5Department of Mathematics, Alagappa University, Karaikudi, IndiaDepartment of Mathematics, Alagappa University, Karaikudi, IndiaDepartment of Mathematics, University of Management and Technology, Lahore, Punjab, PakistanDepartment of Mathematics, College of Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh, Saudi ArabiaDepartment of Mathematics, College of Science, Qassim University, Buraydah, Saudi ArabiaInstitute for Management Information Systems, Suez, EgyptThe significance of clustering algorithms lies in their ability to distinguish problems and devise customized solutions. In the broader context of clustering, fuzzy clustering is one of the crucial aspects. In response to the real-world clustering problems, this research suggests a new fuzzy cluster scheme of data under the linear diophantine fuzzy set(LDFS) framework. More precisely, LDF clustering is initiated with the aid of the correlation coefficient(<inline-formula> <tex-math notation="LaTeX">$\mathcal {CC}$ </tex-math></inline-formula>) and weighted correlation coefficient(<inline-formula> <tex-math notation="LaTeX">$\mathcal {WCC}$ </tex-math></inline-formula>) for LDFS. Due to their ability to quantify the degree of similarity between two elements, <inline-formula> <tex-math notation="LaTeX">$\mathcal {CC}$ </tex-math></inline-formula> are valuable in clustering problems. The LDF- clustering algorithm comprises a well-integrated algorithm for managing uncertainty and <inline-formula> <tex-math notation="LaTeX">$\mathcal {CC}$ </tex-math></inline-formula> among LDFS. Also, our approach to LDF clustering is compared to existing fuzzy clustering studies to assess its effectiveness. Since LDFS broadens the score space, the experimental evaluation of our proposed scheme enables Decision makers(DM) to freely select their score values. The theme of this study is to impart the commencement of LDF-clustering analysis and attempt to apply <inline-formula> <tex-math notation="LaTeX">$\mathcal {CC}$ </tex-math></inline-formula> to the clustering problem. An interpretative example provides the analysis of the logistic efficiency of food products by employing an LDF-clustering algorithm.https://ieeexplore.ieee.org/document/10456891/LDFSclustering algorithmcorrelation coefficientlogisticsfood productsoptimization |
| spellingShingle | Jeevitha Kannan Vimala Jayakumar Muhammad Saeed Tmader Alballa Hamiden Abd El-Wahed Khalifa Heba Ghareeb Gomaa Linear Diophantine Fuzzy Clustering Algorithm Based on Correlation Coefficient and Analysis on Logistic Efficiency of Food Products IEEE Access LDFS clustering algorithm correlation coefficient logistics food products optimization |
| title | Linear Diophantine Fuzzy Clustering Algorithm Based on Correlation Coefficient and Analysis on Logistic Efficiency of Food Products |
| title_full | Linear Diophantine Fuzzy Clustering Algorithm Based on Correlation Coefficient and Analysis on Logistic Efficiency of Food Products |
| title_fullStr | Linear Diophantine Fuzzy Clustering Algorithm Based on Correlation Coefficient and Analysis on Logistic Efficiency of Food Products |
| title_full_unstemmed | Linear Diophantine Fuzzy Clustering Algorithm Based on Correlation Coefficient and Analysis on Logistic Efficiency of Food Products |
| title_short | Linear Diophantine Fuzzy Clustering Algorithm Based on Correlation Coefficient and Analysis on Logistic Efficiency of Food Products |
| title_sort | linear diophantine fuzzy clustering algorithm based on correlation coefficient and analysis on logistic efficiency of food products |
| topic | LDFS clustering algorithm correlation coefficient logistics food products optimization |
| url | https://ieeexplore.ieee.org/document/10456891/ |
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