Research Article
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Year 2024, Volume: 37 Issue: 1, 415 - 425, 01.03.2024
https://doi.org/10.35378/gujs.1013358

Abstract

References

  • [1] Zadeh, L.A., “Fuzzy sets”, Information and Control, 8(3): 338-1150, (1965).
  • [2] Atanassov, K.T., “Intuitionistic fuzzy sets”, Fuzzy Sets and Systems, 20(1): 87-96, (1986).
  • [3] Yager, R.R., “Pythagorean membership grades in multicriteria decision making”, IEEE Transactions on Fuzzy Systems, 22(4): 958-965, (2013).
  • [4] Yager, R.R., “Generalized orthopair fuzzy sets”, IEEE Transactions on Fuzzy Systems, 25(5): 1222-1230, (2016).
  • [5] Petchimuthu, S., Garg, H., Kamacı, H., Atagün, A.O., “The mean operators and generalized products of fuzzy soft matrices and their applications in MCGDM”, Computational and Applied Mathematics, 39(2): 68, (2020).
  • [6] Kamacı, H., “Interval-valued fuzzy parameterized intuitionistic fuzzy soft sets and their applications”, Cumhuriyet Science Journal, 40(2): 317-331, (2019).
  • [7] Jamkhaneh, E.B., “The modified modal operators over the generalized interval valued intuitionistic fuzzy sets”, Gazi University Journal of Science, 32(3): 991-1006, (2019).
  • [8] Chauhan, S., Pant, B., Bhatt, S., “Fixed point theorems for weakly compatible mappings in intuitionistic fuzzy metric spaces”, Gazi University Journal of Science, 26(2): 173-179, (2013).
  • [9] Peng, X., Selvachandran, G., “Pythagorean fuzzy set: state of the art and future directions”, Artificial Intelligence Review, 52: 1873-1927, (2019).
  • [10] Peng, X., Yang, Y., “Some results for Pythagorean fuzzy sets”, International Journal of Intelligent Systems, 30(11): 1133-1160 (2015).
  • [11] Akram, M., Alsulami, S., Karaaslan, F., Khan, A., “q-rung orthopair fuzzy graphs under Hamacher operators”, Journal of Intelligent and Fuzzy Systems, 40(1): 1367-1390, (2021).
  • [12] Riaz, M., Farid, H.M.A., Karaaslan, F., Hashmi, M.R., “Some q-rung orthopair fuzzy hybrid aggregation operators and TOPSIS method for multi-attribute decision-making”, Journal of Intelligent and Fuzzy Systems, 39(1): 1227-1241, (2020).
  • [13] Akram, M., Bashir, A., Edalatpanah, S.A., “A hybrid decision-making analysis under complex q-rung picture fuzzy Einstein averaging operators”, Computational and Applied Mathematics, 40: Article number: 305, (2021).
  • [14] Akram, M., Naz S., Edalatpanah, S.A., Mehreen, R., “Group decision-making framework under linguistic q-rung orthopair fuzzy Einstein models”, Soft Computing, 25: 10309-10334, (2021).
  • [15] Liu, P., Shahzadi, G., Akram, M., “Specific types of q-rung picture fuzzy Yager aggregation operators for decision-making”, International Journal of Computational Intelligence Systems, 13(1): 1072-1091, (2020).
  • [16] Garg, H., Ali, Z., Mahmood T., Aljahdali, S., “Some similarity and distance measures between complex interval-valued q-rung orthopair fuzzy sets based on cosine function and their applications”, Mathematical Problems in Engineering, 2021: 25 pages, (2021).
  • [17] Hung, W.L., Yang M.S., “Similarity measures of intuitionistic fuzzy sets based on Hausdorff distance”, Pattern Recognition Letters, 25: 1603-1611, (2004).
  • [18] Peng, X., Garg, H., “Multiparametric similarity measures on Pythagorean fuzzy sets with applications to pattern recognition”, Applied Intelligence, 49(12): 4058-4096, (2019).
  • [19] Zhang, X.L., “A novel approach based on similarity measure for Pythagorean fuzzy multiple criteria group decision making”, International Journal of Intelligent Systems, 31: 593-611, (2016).
  • [20] Riaz, T., Hashmi, M.R., “Linear Diophantine fuzzy set and its applications towards multi-attribute decision-making problems”, Journal of Intelligent and Fuzzy Systems, 37: 5417-5439, (2019).
  • [21] Kamacı, H., “Linear Diophantine fuzzy algebraic structures”, Journal of Ambient Intelligence and Humanized Computing, 12(11): 10353-10373, (2021).
  • [22] Kamacı, H., “Complex linear Diophantine fuzzy sets and their cosine similarity measures with applications”, Complex and Intelligent Systems, 8: 1281-1305, (2022).
  • [23] Almagrabi, A.O., Abdullah, S., Shams, M., Al-Otaibi, Y.D., Ashraf, S., “A new approach to q-linear Diophantine fuzzy emergency decision support system for COVID19”, Journal of Ambient Intelligence and Humanized Computing, 13: 1687-1713, (2022).
  • [24] Wang, P., Wang, J., Wei, G., Wei, C., “Similarity measures of q-rung orthopair fuzzy sets based on cosine function and their applications”, Mathematics, 7(4): 340, (2019).
  • [25] Nguyen, X.T., Nguyen, V.D., Nguyen, V.H., “Exponential similarity measures for Pythagorean fuzzy sets and their applications to pattern recognition and decision-making process”, Complex and Intelligent Systems, 5: 217-228, (2019).

Exponential Function-Based Similarity Measures for q-Rung Linear Diophantine Fuzzy Sets and Their Application to Clustering Problem

Year 2024, Volume: 37 Issue: 1, 415 - 425, 01.03.2024
https://doi.org/10.35378/gujs.1013358

Abstract

The q-rung linear Diophantine fuzzy set is a recently developed tool to handle with uncertain and vague information in real-life issues and can be applied for reference parameter-based opinions. Similarity measures determine distance with dimensions that represent features of the objects. Despite the importance of exponential function-based similarity measures, there is no satisfactory formulation for q-rung linear Diophantine fuzzy sets in the literature. This paper proposes similarity measures based on exponential function for q-rung linear Diophantine fuzzy sets and thus presents the first formulas for calculating the similarity coefficient between two q-rung linear Diophantine fuzzy sets. The salient features of the new similarity measures are axiomatically addressed to ensure their good performance. Also, they are applied to the clustering problem and the results are analyzed. A comparative study is established and thus several advantages of the proposed similarity measures are discussed.

References

  • [1] Zadeh, L.A., “Fuzzy sets”, Information and Control, 8(3): 338-1150, (1965).
  • [2] Atanassov, K.T., “Intuitionistic fuzzy sets”, Fuzzy Sets and Systems, 20(1): 87-96, (1986).
  • [3] Yager, R.R., “Pythagorean membership grades in multicriteria decision making”, IEEE Transactions on Fuzzy Systems, 22(4): 958-965, (2013).
  • [4] Yager, R.R., “Generalized orthopair fuzzy sets”, IEEE Transactions on Fuzzy Systems, 25(5): 1222-1230, (2016).
  • [5] Petchimuthu, S., Garg, H., Kamacı, H., Atagün, A.O., “The mean operators and generalized products of fuzzy soft matrices and their applications in MCGDM”, Computational and Applied Mathematics, 39(2): 68, (2020).
  • [6] Kamacı, H., “Interval-valued fuzzy parameterized intuitionistic fuzzy soft sets and their applications”, Cumhuriyet Science Journal, 40(2): 317-331, (2019).
  • [7] Jamkhaneh, E.B., “The modified modal operators over the generalized interval valued intuitionistic fuzzy sets”, Gazi University Journal of Science, 32(3): 991-1006, (2019).
  • [8] Chauhan, S., Pant, B., Bhatt, S., “Fixed point theorems for weakly compatible mappings in intuitionistic fuzzy metric spaces”, Gazi University Journal of Science, 26(2): 173-179, (2013).
  • [9] Peng, X., Selvachandran, G., “Pythagorean fuzzy set: state of the art and future directions”, Artificial Intelligence Review, 52: 1873-1927, (2019).
  • [10] Peng, X., Yang, Y., “Some results for Pythagorean fuzzy sets”, International Journal of Intelligent Systems, 30(11): 1133-1160 (2015).
  • [11] Akram, M., Alsulami, S., Karaaslan, F., Khan, A., “q-rung orthopair fuzzy graphs under Hamacher operators”, Journal of Intelligent and Fuzzy Systems, 40(1): 1367-1390, (2021).
  • [12] Riaz, M., Farid, H.M.A., Karaaslan, F., Hashmi, M.R., “Some q-rung orthopair fuzzy hybrid aggregation operators and TOPSIS method for multi-attribute decision-making”, Journal of Intelligent and Fuzzy Systems, 39(1): 1227-1241, (2020).
  • [13] Akram, M., Bashir, A., Edalatpanah, S.A., “A hybrid decision-making analysis under complex q-rung picture fuzzy Einstein averaging operators”, Computational and Applied Mathematics, 40: Article number: 305, (2021).
  • [14] Akram, M., Naz S., Edalatpanah, S.A., Mehreen, R., “Group decision-making framework under linguistic q-rung orthopair fuzzy Einstein models”, Soft Computing, 25: 10309-10334, (2021).
  • [15] Liu, P., Shahzadi, G., Akram, M., “Specific types of q-rung picture fuzzy Yager aggregation operators for decision-making”, International Journal of Computational Intelligence Systems, 13(1): 1072-1091, (2020).
  • [16] Garg, H., Ali, Z., Mahmood T., Aljahdali, S., “Some similarity and distance measures between complex interval-valued q-rung orthopair fuzzy sets based on cosine function and their applications”, Mathematical Problems in Engineering, 2021: 25 pages, (2021).
  • [17] Hung, W.L., Yang M.S., “Similarity measures of intuitionistic fuzzy sets based on Hausdorff distance”, Pattern Recognition Letters, 25: 1603-1611, (2004).
  • [18] Peng, X., Garg, H., “Multiparametric similarity measures on Pythagorean fuzzy sets with applications to pattern recognition”, Applied Intelligence, 49(12): 4058-4096, (2019).
  • [19] Zhang, X.L., “A novel approach based on similarity measure for Pythagorean fuzzy multiple criteria group decision making”, International Journal of Intelligent Systems, 31: 593-611, (2016).
  • [20] Riaz, T., Hashmi, M.R., “Linear Diophantine fuzzy set and its applications towards multi-attribute decision-making problems”, Journal of Intelligent and Fuzzy Systems, 37: 5417-5439, (2019).
  • [21] Kamacı, H., “Linear Diophantine fuzzy algebraic structures”, Journal of Ambient Intelligence and Humanized Computing, 12(11): 10353-10373, (2021).
  • [22] Kamacı, H., “Complex linear Diophantine fuzzy sets and their cosine similarity measures with applications”, Complex and Intelligent Systems, 8: 1281-1305, (2022).
  • [23] Almagrabi, A.O., Abdullah, S., Shams, M., Al-Otaibi, Y.D., Ashraf, S., “A new approach to q-linear Diophantine fuzzy emergency decision support system for COVID19”, Journal of Ambient Intelligence and Humanized Computing, 13: 1687-1713, (2022).
  • [24] Wang, P., Wang, J., Wei, G., Wei, C., “Similarity measures of q-rung orthopair fuzzy sets based on cosine function and their applications”, Mathematics, 7(4): 340, (2019).
  • [25] Nguyen, X.T., Nguyen, V.D., Nguyen, V.H., “Exponential similarity measures for Pythagorean fuzzy sets and their applications to pattern recognition and decision-making process”, Complex and Intelligent Systems, 5: 217-228, (2019).
There are 25 citations in total.

Details

Primary Language English
Subjects Engineering
Journal Section Mathematics
Authors

Subramanian Petchımuthu This is me 0000-0003-4318-5044

Hüseyin Kamacı 0000-0002-0429-6713

Early Pub Date August 28, 2023
Publication Date March 1, 2024
Published in Issue Year 2024 Volume: 37 Issue: 1

Cite

APA Petchımuthu, S., & Kamacı, H. (2024). Exponential Function-Based Similarity Measures for q-Rung Linear Diophantine Fuzzy Sets and Their Application to Clustering Problem. Gazi University Journal of Science, 37(1), 415-425. https://doi.org/10.35378/gujs.1013358
AMA Petchımuthu S, Kamacı H. Exponential Function-Based Similarity Measures for q-Rung Linear Diophantine Fuzzy Sets and Their Application to Clustering Problem. Gazi University Journal of Science. March 2024;37(1):415-425. doi:10.35378/gujs.1013358
Chicago Petchımuthu, Subramanian, and Hüseyin Kamacı. “Exponential Function-Based Similarity Measures for Q-Rung Linear Diophantine Fuzzy Sets and Their Application to Clustering Problem”. Gazi University Journal of Science 37, no. 1 (March 2024): 415-25. https://doi.org/10.35378/gujs.1013358.
EndNote Petchımuthu S, Kamacı H (March 1, 2024) Exponential Function-Based Similarity Measures for q-Rung Linear Diophantine Fuzzy Sets and Their Application to Clustering Problem. Gazi University Journal of Science 37 1 415–425.
IEEE S. Petchımuthu and H. Kamacı, “Exponential Function-Based Similarity Measures for q-Rung Linear Diophantine Fuzzy Sets and Their Application to Clustering Problem”, Gazi University Journal of Science, vol. 37, no. 1, pp. 415–425, 2024, doi: 10.35378/gujs.1013358.
ISNAD Petchımuthu, Subramanian - Kamacı, Hüseyin. “Exponential Function-Based Similarity Measures for Q-Rung Linear Diophantine Fuzzy Sets and Their Application to Clustering Problem”. Gazi University Journal of Science 37/1 (March 2024), 415-425. https://doi.org/10.35378/gujs.1013358.
JAMA Petchımuthu S, Kamacı H. Exponential Function-Based Similarity Measures for q-Rung Linear Diophantine Fuzzy Sets and Their Application to Clustering Problem. Gazi University Journal of Science. 2024;37:415–425.
MLA Petchımuthu, Subramanian and Hüseyin Kamacı. “Exponential Function-Based Similarity Measures for Q-Rung Linear Diophantine Fuzzy Sets and Their Application to Clustering Problem”. Gazi University Journal of Science, vol. 37, no. 1, 2024, pp. 415-2, doi:10.35378/gujs.1013358.
Vancouver Petchımuthu S, Kamacı H. Exponential Function-Based Similarity Measures for q-Rung Linear Diophantine Fuzzy Sets and Their Application to Clustering Problem. Gazi University Journal of Science. 2024;37(1):415-2.