|تعداد مشاهده مقاله||9,731,577|
|تعداد دریافت فایل اصل مقاله||6,362,976|
A Hybridized Correlation Coefficient Technique and its Application in Classification Process under Intuitionistic Fuzzy Setting
|Iranian Journal of Fuzzy Systems|
|دوره 20، شماره 4، مهر و آبان 2023، صفحه 103-120 اصل مقاله (232.11 K)|
|نوع مقاله: Research Paper|
|شناسه دیجیتال (DOI): 10.22111/ijfs.2023.42888.7508|
|Paul Augustine Ejegwa* 1؛ Chinelo Francisca Ajogwu1؛ Arun Sarkar2|
|1Department of Mathematics, University of Agriculture, P.M.B. 2373, Makurdi, Nigeria|
|2Department of Mathematics, Heramba Chandra College, Kolkata - 700029, Indian|
|Intuitionistic fuzzy set (IFS) is a reliable device for resolving uncertainty and haziness encountered in decision-making process. In most cases, the significance of IFSs are explored based on correlation measures in myriad of areas like in engineering, image segmentation, pattern recognition, diagnostic|
analysis, etc. Some methods for computing intuitionistic fuzzy correlation coefficient (IFCC) have been investigated, however with some inadequacies. In this present work, a new method of IFCC is developed to correct the drawbacks in some existing techniques in terms of mathematical presentation and the exclusion of the hesitation parameter to enhance reasonable output. A comparative analysis is presented to ascertain the edge of the new technique over some similar
approaches. In addition, the new correlation coefficient technique is applied to discuss some pattern recognition problems. This new IFCC method could be investigated based on spherical fuzzy data, q-rung orthopair fuzzy data, and picture fuzzy data.
|Correlation measure؛ Intuitionistic fuzzy sets؛ Decision-making؛ Intuitionistic fuzzy pairs؛ Pattern recognition|
 K. T. Atanassov, Intuitionistic fuzzy sets, Fuzzy Sets and Systems, 20 (1986), 87-96.
 K. T. Atanassov, E. Szmidt, J. Kacprzyk, On intuitionistic fuzzy pairs, Notes on Intuitionistic Fuzzy Sets, 19(3)(2013), 1-13.
 F. E. Boran, D. Akay, A biparametric similarity measure on intuitionistic fuzzy sets with applications to pattern recognition, Information Sciences, 255(10) (2014), 45-57.
 S. M. Chen, C. H. Chang, A novel similarity measure between Atanassov's intuitionistic fuzzy sets based on trans-formation techniques with applications to pattern recognition, Information Sciences, 291 (2015), 96-114.
 C. Chen, X. Deng, Several new results based on the study of distance measures of intuitionistic fuzzy sets, Iranian Journal of Fuzzy Systems, 17(2) (2020), 147-163.
 M. Citil, Application of the intuitionistic fuzzy logic in education, Communications in Mathematics and Applications, 10(1) (2019), 131-143.
 S. Das, S. Kar, T. Pal, Robust decision making using intuitionistic fuzzy numbers, Granular Computing, 2 (2017), 41-54.
 B. Davvaz, E. H. Sadrabadi, An application of intuitionistic fuzzy sets in medicine, International Journal of Biomathatics, 9(3) (2016), 1650037 (15 pages).
 S. K. De, R. Biswas, A. R. Roy, An application of intuitionistic fuzzy sets in medical diagnosis, Fuzzy Sets and Systems, 117(2) (2001), 209-213.
 L. Dengfeng, C. Cheng, New similarity measures of intuitionistic fuzzy sets and application to pattern recognitions, Pattern Recognition Letters, 23 (2002), 221-225.
 J. Duan, X. Li, Similarity of intuitionistic fuzzy sets and its applications, International Journal of Approximate Reasoning, 137 (2021), 166-180.
 P. A. Ejegwa, Novel correlation coefficient for intuitionistic fuzzy sets and its application to multi-criteria decision-making problems, International Journal of Fuzzy System and Applications, 10(2) (2021), 39-58.
 P. A. Ejegwa, J. M. Agbetayo, Similarity-distance decision-making technique and its applications via intuitionistic fuzzy pairs, Journal of Computational and Cognitive Engineering, 2(1) (2023), 68-74.
 P. A. Ejegwa, S. Ahemen, Enhanced intuitionistic fuzzy similarity operator with applications in emergency man-agement and pattern recognition, Granular Computing, 8 (2023), 361-372.
 P. A. Ejegwa, A. J. Akubo, O. M. Joshua, Intuitionistic fuzzzy sets in career determination, Journal of Information and Computing Science, 9(4) (2014), 285-288.
 P. A. Ejegwa, I. C. Onyeke, Medical diagnostic analysis on some selected patients based on modified Thao et al.'s correlation coefficient of intuitionistic fuzzy sets via an algorithmic approach, Journal of Fuzzy Extensions and Application, 1(2) (2020), 130-141.
 P. A. Ejegwa, I. C. Onyeke, Intuitionistic fuzzy statistical correlation algorithm with applications to multi-criteria based decision-making processes, International Journal of Intelligent Systems, 36(3) (2021), 1386-1407.
 P. A. Ejegwa, I. C. Onyeke, A novel intuitionistic fuzzy correlation algorithm and its applications in pattern recognition and student admission process, International Journal of Fuzzy System and Applications, 11(1) (2022). DOI:10.4018/IJFSA.285984.
 P. A. Ejegwa, I. C. Onyeke, V. Adah, An algorithm for an improved intuitionistic fuzzy correlation measure with medical diagnostic application, Annals of Optimization Theory and Practice, 3(3) (2020), 51-66.
 P. A. Ejegwa, I. C. Onyeke, N. Kausar, P. Kattel, A new partial correlation coefficient technique based on intuition-istic fuzzy information and its pattern recognition application, International Journal of Intelligent Systems, (2023), 14 pages. DOI:10.1155/2023/5540085.
 P. A. Ejegwa, I. C. Onyeke, B. T. Terhemen, M. P. Onoja, A. Ogiji, C. U. Opeh, Modified Szmidt and Kacprzyk's intuitionistic fuzzy distances and their applications in decision-making, Journal of Nigerian Society of Physical Sciences, 4 (2022), 175-182.
 H. Garg, R. Arora, TOPSIS method based on correlation coefficient for solving decision-making problems with intuitionistic fuzzy soft set information, AIMS Mathematics, 5(4) (2020), 2944-2966.
 H. Garg, K. Kumar, A novel correlation coefficient of intuitionistic fuzzy sets based on the connection number of set pair analysis and its application, Scientia Iranica, 25(4) (2018), 2373-2388.
 T. Gerstenkorn, J. Manko, Correlation of intuitionistic fuzzy sets, Fuzzy Sets and Systems, 44(1) (1991), 39-43.
 X. Gu, Y. Ma, Q. Wu, Y. Liu, The application of intuitionistic fuzzy set-TOPSIS model on the level assessment of the surrounding socks, Shock and Vibration, (2022). DOI:10.1155/2022/4263276.
 R. Gupta, S. Kumar, Intuitionistic fuzzy scale-invariant entropy with correlation coefficients based VIKOR approach for multi-criteria decision-making, Granular Computing, 7 (2022), 77-93.
 A. G. Hatzimichailidis, A. G. Papakostas, V. G. Kaburlasos, A novel distance measure of intuitionistic fuzzy sets and its application to pattern recognition problems, International Journal of Intelligent Systems, 27 (2012), 396-409.
 D. H. Hong, S. Y. Hwang, Correlation of intuitionistic fuzzy sets in probability spaces, Fuzzy Sets and Systems, 75 (1995), 77-81.
 H. L. Huang, Y. Guo, An improved correlation coefficient of intuitionistic fuzzy sets, Journal of Intelligent Systems, 28(2) (2019), 231-243.
 W. L. Hung, Using statistical viewpoint in developing correlation of intuitionistic fuzzy sets, International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 9(4) (2001), 509-516.
 W. L. Hung, J. W. Wu, Correlation of intuitionistic fuzzy sets by centroid method, Information Sciences, 144(1)(2002), 219-225.
 C. M. Hwang, M. S. Yang, New construction for similarity measures between intuitionistic fuzzy sets based on lower, upper and middle fuzzy sets, International Journal of Fuzzy Systems, 15(3) (2013), 359-366.
 M. N. Iqbal, U. Rizwan, Some applications of intuitionistic fuzzy sets using new similarity measure, Journal of Ambient Intelligent and Humanized Computing, (2019). DOI:10.1007/s12652-019-01516-7.
 T. Johnson, Applications of intuitionistic fuzzy sets in the academic career of the students, Indian Journal of Science and Technology, 10(34) (2017), 1-5.
 A. M. Kozae, M. Shokry, M. Omran, Intuitionistic fuzzy set and its application in Corona Covid-19, Applied Computational Mathematics, 9(5) (2020), 146-154.
 Z. Liang, P. Shi, Similarity measures on intuitionistic fuzzy sets, Pattern Recognition Letters, 24 (2003), 2687-2693.
 P. Liu, S. M. Chen, Group decision making based on Heronian aggregation operators of intuitionistic fuzzy numbers, IEEE Transaction on Cybernetics, 47(9) (2017), 2514-2530.
 B. Liu, Y. Shen, L. Mu, X. Chen, L. Chen, A new correlation measure of the intuitionistic fuzzy sets, Journal of Intelligent and Fuzzy Systems, 30(2) (2016), 1019-1028.
 M. Pant, S. Kumar, Particle swarm optimization and intuitionistic fuzzy set-based novel method for fuzzy time series forecasting, Granular Computing, 7 (2022), 285-303.
 J. H. Park, K. M. Lim, J. S. Park, Y. C. Kwun, Correlation coefficient between intuitionistic fuzzy sets, In: Cao B, Li TF, Zhang CY (Eds.): AISC 62, Fuzzy Information and Engineering, Springer, Berlin, Heidelberg, 2 (2009), 601-610.
 T. D. Quynh, N. X. Thao, N. Q. Thuan, N. V. Dinh, A new similarity measure of IFSs and its applications, In: Proceedings of the 12th International Conference of Knowledge and Systems Engineering, Vietnam, 2020.
 V. Ranjbar, G. Hesamian, Copula function for fuzzy random variables: Applications in measuring association between two fuzzy random variables, Statistical Papers, 61(1) (2020), 503-522.
 M. R. Seikh, U. Manda, Intuitionistic fuzzy Dombi aggregation operators and their application to multiple attribute decision-making, Granular Computing, 6 (2021), 473-488.
 A. Sheikhi, R. Mesiar, M. Holena, A dimension reduction in neural network using copula matrix, International Journal of General Systems, (2022). DOI: 10.1080/03081079.2022.2108029.
 E. Szmidt, J. Kacprzyk, Medical diagnostic reasoning using a similarity measure for intuitionistic fuzzy sets, Notes on Intuitionistic Fuzzy Sets, 10(4) (2004), 61-69.
 E. Szmidt, J. Kacprzyk, Correlation of intuitionistic fuzzy sets, In: Hullermeier E., Kruse R., Hoffmann (Eds.): IPMU, LNAI, Springer, Berlin, Heidelberg. 6178 (2010), 169-177.
 E. Szmidt, J. Kacprzyk, P. Bujnowski, Attribute selection via Hellwig's for Atanassov's intuitionistic fuzzy sets, In: L. T. Koczy et al. (eds.), Computational Intelligence and Mathematics for Tackling Complex Problems, Studies in Computational Intelligence, Springer Nature Switzerland AG, 819 (2020), 81-90.
 N. X. Thao, A new correlation coefficient of the intuitionistic fuzzy sets and its application, Journal of Intelligent and Fuzzy Systems, 35(2) (2018), 1959-1968.
 N. X. Thao, M. Ali, F. Smarandache, An intuitionistic fuzzy clustering algorithm based on a new correlation coefficient with application in medical diagnosis, Journal of Intelligent and Fuzzy Systems, 36(1) (2019), 189-198.
 W. Wang, X. Xin, Distance measure between intuitionistic fuzzy sets, Pattern Recognition Letters, 26 (2005), 2063-2069.
 Z. S. Xu, On correlation measures of intuitionistic fuzzy sets, In: Corchado, E. et al. (eds.): IDEAL 2006, LNCS 4224, Springer-Verlag Berlin Heidelberg, (2006), 16-24.
 Z. S. Xu, X. Q. Cai, Correlation, distance and similarity measures of intuitionistic fuzzy sets, In: Intuitionistic Fuzzy Information Aggregation, Springer, Berlin, Heidelberg, (2012), 151-188.
 Z. S. Xu, J. Chen, J. J. Wu, Cluster algorithm for intuitionistic fuzzy sets, Information Sciences, 178 (2008), 3775-3790.
 P. C. P. Yen, K. C. Fan, H. C. J. Chao, A new method for similarity measures for pattern recognition, Applied Mathematical Modelling, 37 (2013), 5335-5342.
 L. A. Zadeh, Fuzzy sets, Information Control, 8 (1965), 338-353.
 W. Y. Zeng, H. S. Cui, Y. Q. Liu, Q. Yin, Z. S. Xu, Novel distance measure between intuitionistic fuzzy sets and its application in pattern recognition, Iranian Journal of Fuzzy Systems, 19(3) (2022), 127-137.
 W. Zeng, H. Li, Correlation coecient of intuitionistic fuzzy sets, Journal of Industrial and Engineering International, 3(5) (2007), 33-40.
 H. Zhang, J. Xie, Y. Song, J. Ge, Z. Zhang, A novel ranking method for intuitionistic fuzzy set based on information fusion and application to threat assessment, Iranian Journal of Fuzzy Systems, 17(1) (2020), 91-104.
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