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Randić energies for T-spherical fuzzy Hamacher graphs and their applications in decision making for business plans

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Abstract

To imitate the uncertainty and ambiguity in various decision-making problems, the T-spherical fuzzy set is more pragmatic and influential than the picture fuzzy set and q-rung orthopair fuzzy set. Because of the vagueness and fuzziness found in real-life problems, in which intuitionistic fuzzy sets may not give adequate results, the T-spherical fuzzy set is an efficient mathematical model to deal with them and can be handled effectively by using the notion of T-spherical fuzzy sets. In a different framework which is based on more opinions like yes, no, refusal, and abstaining, the T-spherical fuzzy set has been proven to be the most beneficial. In this article, we proposed the idea of T-spherical fuzzy Hamacher graphs (TSFHGs) based on Hamacher t-norm and t-conorm. We investigate the notion of the energy of TSFHGs, splitting TSFHGs, and shadow TSFHGs. Further, we introduce the Randić energy of TSFHG and studied its fundamental results. Moreover, we introduced the T-spherical fuzzy Hamacher digraphs (TSFHDGs) and discussed various results. We studied the applications of the proposed energies of TSFHGs in a decision-making problem by using an algorithm involving TSFHDGs and Hamacher aggregation operators. We also established a comparative study to see the significance of our proposed results.

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References

  • Akram M, Sattar A, Karaaslan F, Samanta S (2020) Extension of competition graphs under complex fuzzy environment. Complex Intell Syst 7(1):539–558

    Article  Google Scholar 

  • Akram M, Naz S, Edalatpanah SA, Mehreen R (2021) Group decision-making framework under linguistic q-rung orthopair fuzzy einstein models. Soft Comput 25(15):10309–10334

    Article  MATH  Google Scholar 

  • Akram M, Rukhsar UA, Karaaslan F (2021) Complex pythagorean fuzzy threshold graphs with application in petroleum replenishment. J Appl Math Comput 68(3):2125–2150

    Article  MathSciNet  MATH  Google Scholar 

  • Akram M, Alsulami S, Karaaslan F, Khan A (2021) q-rung orthopair fuzzy graphs under hamacher operators. J Intell Fuzzy Syst 40(1):1367–1390

    Article  Google Scholar 

  • Akram M, Ullah K, Pamucar D (2022) Performance evaluation of solar energy cells using the interval-valued t-spherical fuzzy bonferroni mean operators. Energies 15(1):292

    Article  Google Scholar 

  • Atanassov KT (1999) Intuitionistic fuzzy sets. In: Intuitionistic Fuzzy Sets, pages 1–137. Physica-Verlag HD

  • Cuong BC, Kreinovich V (2013) Picture fuzzy sets—a new concept for computational intelligence problems. In: 2013 Third World Congress on Information and Communication Technologies (WICT 2013). IEEE, dec 2013

  • Deng H, Sun X, Liu M, Ye C, Zhou X (2016) Image enhancement based on intuitionistic fuzzy sets theory. IET Image Process 10(10):701–709

    Article  Google Scholar 

  • Fayazi F, Rahimi Sharbaf S (2014) Laplacian energy of a fuzzy graph. Iran J Math Chem 5

  • Garg H (2016) A new generalized pythagorean fuzzy information aggregation using einstein operations and its application to decision making. Int J Intell Syst 31(9):886–920

    Article  Google Scholar 

  • Guleria A, Bajaj RK (2019) T-spherical fuzzy graphs: operations and applications in various selection processes. Arab J Sci Eng 45(3):2177–2193

    Article  Google Scholar 

  • Habib A, Akram M, Farooq A (2019) q-rung orthopair fuzzy competition graphs with application in the soil ecosystem. Mathematics 7(1):91

    Article  MathSciNet  Google Scholar 

  • Hamacher H (1975) ber logische verknpfungen unscharfer aussagen und deren zugehrige bewertungsfunktionen. RWTH Aachen, West Germany

    Google Scholar 

  • Hameed S, Akram M, Mustafa N, Samanta S (2021) Extension of threshold graphsunder complex fuzzy environment. Int J Appl Comput Math 7(5):1–19

    Article  MATH  Google Scholar 

  • Hayat S, Khan S (2021) Quality testing of spectrum-based valency descriptors for polycyclic aromatic hydrocarbons with applications. J Mol Struct 1228:129789

    Article  Google Scholar 

  • Jurio A, Paternain D, Bustince H, Guerra C, Beliakov G (2010) A construction method of atanassovs intuitionistic fuzzy sets for image processing. In: 2010 5th IEEE International Conference Intelligent Systems. IEEE

  • Kaufman A (1973) Theorie des sous-ensembles fous. Masson et Cie, Paris

  • Lavanya T, Amsaveni D (2020) Spherical fuzzy graph. Malaya J Matematik 8(4):1966–1969

    Article  MathSciNet  Google Scholar 

  • Lin M, Wei J, Zeshui X, Chen R (2018) Multiattribute group decision-making based on linguistic pythagorean fuzzy interaction partitioned bonferroni mean aggregation operators. Complexity 2018:1–24

    MATH  Google Scholar 

  • Lin M, Li X, Chen L (2019) Linguistic q-rung orthopair fuzzy sets and their interactional partitioned heronian mean aggregation operators. Int J Intell Syst 35(2):217–249

    Article  Google Scholar 

  • Lin M, Wang H, Zeshui X (2019) TODIM-based multi-criteria decision-making method with hesitant fuzzy linguistic term sets. Artif Intell Rev 53(5):3647–3671

    Article  Google Scholar 

  • Lin M, Huang C, Zeshui X (2019) TOPSIS method based on correlation coefficient and entropy measure for linguistic pythagorean fuzzy sets and its application to multiple attribute decision making. Complexity 2019:1–16

    MATH  Google Scholar 

  • Lin M, Huang C, Zeshui X (2020) MULTIMOORA based MCDM model for site selection of car sharing station under picture fuzzy environment. Sustain Cities Soc 53:101873

    Article  Google Scholar 

  • Mahmood T, Ullah K, Khan Q, Jan N (2018) An approach toward decision-making and medical diagnosis problems using the concept of spherical fuzzy sets. Neural Comput Appl 31(11):7041–7053

    Article  Google Scholar 

  • Mathew S, Anjali N (2013) Energy of a fuzzy graph. Ann Fuzzy Math Inform

  • Melo-Pinto P, Couto P, Bustince H, Barrenechea E, Pagola M, Fernandez Javier (2013) Image segmentation using atanassov’s intuitionistic fuzzy sets. Expert Syst Appl 40(1):15–26

    Article  MATH  Google Scholar 

  • Naz S, Ashraf S, Karaaslan F (2018) Energy of a bipolar fuzzy graph and itsapplication in decision making. Ital J Pure Appl Math 40:339–352

    Google Scholar 

  • Naz S, Ashraf S, Akram M (2018) A novel approach to decision-making with pythagorean fuzzy information. Mathematics 6(6):95

    Article  MATH  Google Scholar 

  • Palaniappan N, Srinivasan R (2009) Applications of intuitionistic fuzzy sets of root type in image processing. In: NAFIPS 2009 - 2009 Annual Meeting of the North American Fuzzy Information Processing Society. IEEE

  • Parvathi R, Karunambigai MG (2023) Intuitionistic fuzzy graphs. In: Computational Intelligence, Theory and Applications, pages 139–150. Springer Berlin Heidelberg

  • Peter ME, Radko K, Endre P (2000) Triangular norms. Springer, Netherlands

    MATH  Google Scholar 

  • Rosenfeld A (1975) Fuzzy graphs. In: Fuzzy Sets and their Applications to Cognitive and Decision Processes, pages 77–95. Elsevier

  • Sharief BS, Kartheek E (2015) Laplacian energy of an intuitionistic fuzzy graph. Indian J Sci Technol 8(33)

  • Ullah K, Mahmood T, Garg H (2020) Evaluation of the performance of search and rescue robots using t-spherical fuzzy hamacher aggregation operators. Int J Fuzzy Syst 22(2):570–582

    Article  Google Scholar 

  • Vaidya Samir K, Popat Kalpesh M (2017) Some new results on energy of graphs. MATCH Commun Math Comput Chem

  • Vlachos IK, Sergiadis GD (2007) Intuitionistic fuzzy information-applications to pattern recognition. Pattern Recogn Lett 28(2):197–206

    Article  Google Scholar 

  • Yager RR (2014) Pythagorean membership grades in multicriteria decision making. IEEE Trans Fuzzy Syst 22(4):958–965

    Article  Google Scholar 

  • Yager RR (2017) Generalized orthopair fuzzy sets. IEEE Transa Fuzzy Syst 25(5):1222–1230

    Article  Google Scholar 

  • Zadeh LA (1996) Fuzzy sets. In: Advances in Fuzzy Systems-Applications and Theory, pages 394–432. World Scientific

  • Zhoua B, Gutmanb I (2006) On laplacian energy of graphs. MATCH Commun Math Comput Chem

  • Zuo C, Pal A, Dey A (2019) New concepts of picture fuzzy graphs with application. Mathematics 7(5):470

    Article  Google Scholar 

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Acknowledgements

Princess Nourah bint Abdulrahman University Researchers Supporting Project number (PNURSP2023R192), Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia.

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Correspondence to Muhammad Azeem.

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Communicated by Graçaliz Pereira Dimuro.

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Asif, K., Jamil, M.K., Karamti, H. et al. Randić energies for T-spherical fuzzy Hamacher graphs and their applications in decision making for business plans. Comp. Appl. Math. 42, 106 (2023). https://doi.org/10.1007/s40314-023-02243-8

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  • DOI: https://doi.org/10.1007/s40314-023-02243-8

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