Research article

A uniform interval-valued intuitionistic fuzzy environment: topological descriptors and their application in neural networks

  • Received: 16 August 2024 Revised: 27 September 2024 Accepted: 09 October 2024 Published: 12 October 2024
  • MSC : 05C10, 05C50, 05C70, 05C90, 15A18, 15A90, 74E40, 74F25

  • The concept of being uniform strong interval-valued intuitionistic fuzzy (also termed as USIVIF) is an integration of two ideologies, which are called "uniformity" and "strong interval-valued intuitionistic fuzzy sets". Inspired by the study on uniform fuzzy topological indices, it is natural to introduce uniform IVIFTIs. Originally, topological indices were generalized for the fuzzy sets However, the utilization of the interval-valued intuitionistic fuzzy topological indices provides a finer approach, especially if there are multiple uncertainties based on intervals. Consequently, both theories imply that topological indices are not fixed and depend on certain situations or problems in the question. In this article, the generalized results for the uniform degree of the fuzzy sets associated with individual vertices/edges of strong interval-valued intuitionistic fuzzy graphs were presented and results for the total uniform degree of such graphs were also included. In addition, the nature of the implemented methods and models was discussed based on the cellular neural interval-valued intuitionistic fuzzy graphs of sets of membership and non-membership values.

    Citation: Ali Al Khabyah, Haseeb Ahmad, Ali Ahmad, Ali N. A. Koam. A uniform interval-valued intuitionistic fuzzy environment: topological descriptors and their application in neural networks[J]. AIMS Mathematics, 2024, 9(10): 28792-28812. doi: 10.3934/math.20241397

    Related Papers:

  • The concept of being uniform strong interval-valued intuitionistic fuzzy (also termed as USIVIF) is an integration of two ideologies, which are called "uniformity" and "strong interval-valued intuitionistic fuzzy sets". Inspired by the study on uniform fuzzy topological indices, it is natural to introduce uniform IVIFTIs. Originally, topological indices were generalized for the fuzzy sets However, the utilization of the interval-valued intuitionistic fuzzy topological indices provides a finer approach, especially if there are multiple uncertainties based on intervals. Consequently, both theories imply that topological indices are not fixed and depend on certain situations or problems in the question. In this article, the generalized results for the uniform degree of the fuzzy sets associated with individual vertices/edges of strong interval-valued intuitionistic fuzzy graphs were presented and results for the total uniform degree of such graphs were also included. In addition, the nature of the implemented methods and models was discussed based on the cellular neural interval-valued intuitionistic fuzzy graphs of sets of membership and non-membership values.



    加载中


    [1] U. Ahmad, T. Batool, Domination in rough fuzzy digraphs with application, Soft Comput., 27 (2023), 2425–2442. http://dx.doi.org/10.1007/s00500-022-07795-1 doi: 10.1007/s00500-022-07795-1
    [2] U. Ahmad, I. Nawaz, Directed rough fuzzy graph with application to trade networking, Comp. Appl. Math., 41 (2022), 366. http://dx.doi.org/10.1007/s40314-022-02073-0 doi: 10.1007/s40314-022-02073-0
    [3] M. Akram, R. Akmal, Operations on intuitionistic fuzzy graph structures, Fuzzy Information and Engineering, 8 (2016), 389–410. http://dx.doi.org/10.1016/j.fiae.2017.01.001 doi: 10.1016/j.fiae.2017.01.001
    [4] M. Akram, N. Alshehri, Intuitionistic fuzzy cycles and intuitionistic fuzzy trees, Sci. World J., 2014 (2014), 305836. http://dx.doi.org/10.1155/2014/305836 doi: 10.1155/2014/305836
    [5] M. Akram, B. Davvaz, Strong intuitionistic fuzzy graphs, Filomat, 26 (2012), 177–196. http://dx.doi.org/10.2298/FIL1201177A doi: 10.2298/FIL1201177A
    [6] M. Akram, W. Dudek, Intuitionistic fuzzy hypergraphs with applications, Inform. Sciences, 218 (2013), 182–193. http://dx.doi.org/10.1016/j.ins.2012.06.024 doi: 10.1016/j.ins.2012.06.024
    [7] N. Alshehri, M. Akram, Intuitionistic fuzzy planar graphs, Discrete Dyn. Nat. Soc., 2014 (2014), 397823. http://dx.doi.org/10.1155/2014/397823 doi: 10.1155/2014/397823
    [8] K. Atanassov, Intuitionistic fuzzy sets: theory and applications, Heidelberg: Physica-Verlag, 1999. http://dx.doi.org/10.1007/978-3-7908-1870-3
    [9] P. Bhattacharya, Some remarks on fuzzy graphs, Pattern Recogn. Lett., 6 (1987), 297–302. http://dx.doi.org/10.1016/0167-8655(87)90012-2 doi: 10.1016/0167-8655(87)90012-2
    [10] A. Bozhenyuk, S. Belyakov, M. Knyazeva, I. Rozenberg, On computing domination set in intuitionistic fuzzy graph, Int. J. Comput. Int. Sys., 14 (2021), 617–624. http://dx.doi.org/10.2991/ijcis.d.210114.002 doi: 10.2991/ijcis.d.210114.002
    [11] A. Bozhenyuk, S. Belyakov, J. Kacprzyk, M. Knyazeva, The method of finding the base set of intuitionistic fuzzy graph, In: Intelligent and fuzzy techniques: smart and innovative solutions, Cham: Springer, 2020, 18–25. http://dx.doi.org/10.1007/978-3-030-51156-2_3
    [12] M. Chakraborty, T. Ahsanullah, Fuzzy topology on fuzzy sets and tolerance topology, Fuzzy Set. Syst., 45 (1992), 103–108. http://dx.doi.org/10.1016/0165-0114(92)90096-M doi: 10.1016/0165-0114(92)90096-M
    [13] Q. Chen, L. Yang, Y. Zhao, Y. Wang, H. Zhou, X. Chen, Shortest path in leo satellite constellation networks: an explicit analytic approach, IEEE J. Sel. Area. Commun., 42 (2024), 1175–1187. http://dx.doi.org/10.1109/JSAC.2024.3365873 doi: 10.1109/JSAC.2024.3365873
    [14] W. Chen, S. Feng, W. Yin, Y. Li, J. Qian, Q. Chen, et al., Deep-learning-enabled temporally super-resolved multiplexed fringe projection profilometry: high-speed khz 3D imaging with low-speed camera, PhotoniX, 5 (2024), 25. http://dx.doi.org/10.1186/s43074-024-00139-2 doi: 10.1186/s43074-024-00139-2
    [15] P. Das, Fuzzy topology on fuzzy sets: Product fuzzy topology and fuzzy topological groups, Fuzzy Set. Syst., 100 (1998), 367–372. http://dx.doi.org/10.1016/S0165-0114(97)00070-5 doi: 10.1016/S0165-0114(97)00070-5
    [16] J. Dinar, Z. Hussain, S. Zaman, S. Ur Rehman, Wiener index for an intuitionistic fuzzy graph and its application in water pipeline network, Ain Shams Eng. J., 14 (2023), 101826. http://dx.doi.org/10.1016/j.asej.2022.101826 doi: 10.1016/j.asej.2022.101826
    [17] A. Nagoor Gani, S. Latha, On irregular fuzzy graphs, Applied Mathematical Sciences, 6 (2012), 517–523.
    [18] M. Ghods, Z. Rostami, Introduction to topological indices in neutrosophic graphs, Neutrosophic Set. Syst., 35 (2024), 68–77.
    [19] H. Guan, F. Ejaz, A. Ur Rehman, M. Hussain, S. Kosari, Fuzzy topological invariants in uniform fuzzy graphs, J. Intell. Fuzzy Syst., 45 (2023), 1653–1662. http://dx.doi.org/10.3233/JIFS-223402 doi: 10.3233/JIFS-223402
    [20] R. Ameziane Hassani, A. Blali, A. El Amrani, A. Razouki, Fuzzy sequential topology, Proyecciones, 41 (2022), 1505–1521. http://dx.doi.org/10.22199/issn.0717-6279-5330 doi: 10.22199/issn.0717-6279-5330
    [21] A. Hussain, H. Wang, K. Ullah, H. Garg, D. Pamucar, Maclaurin symmetric mean aggregation operators based on novel frank t-norm and t-conorm for intuitionistic fuzzy multiple attribute group decision-making, Alex. Eng. J., 71 (2023), 535–550. http://dx.doi.org/10.1016/j.aej.2023.03.063 doi: 10.1016/j.aej.2023.03.063
    [22] Y. Jin, L. Lu, S. Zhou, J. Zhou, Y. Fan, C. Zuo, Neural-field-assisted transport-of-intensity phase microscopy: partially coherent quantitative phase imaging under unknown defocus distance, Photonics Res., 12 (2024), 1494–1501. http://dx.doi.org/10.1364/PRJ.521056 doi: 10.1364/PRJ.521056
    [23] S. Kalathian, S. Ramalingam, S. Raman, N. Srinivasan, Some topological indices in fuzzy graphs, In: Intelligent and fuzzy techniques in big data analytics and decision making, Cham: Springer, 2019, 73–81. http://dx.doi.org/10.1007/978-3-030-23756-1_11
    [24] S. Kalathian, S. Ramalingam, S. Raman, N. Srinivasan, Some topological indices in fuzzy graphs, J. Intell. Fuzzy Syst., 39 (2020), 6033–6046. http://dx.doi.org/10.3233/JIFS-189077 doi: 10.3233/JIFS-189077
    [25] M. Khalifeh, H. Yousefi-Azari, A. Ashrafi, The first and second zagreb indices of some graph operations, Discrete Appl. Math., 157 (2009), 804–811. http://dx.doi.org/10.1016/j.dam.2008.06.015 doi: 10.1016/j.dam.2008.06.015
    [26] F. Kutlu, O. Atan, O. Silahtar, Intuitionistic fuzzy adaptive sliding mode control of nonlinear systems, Soft Comput., 24 (2020), 53–64. http://dx.doi.org/10.1007/s00500-019-04286-8 doi: 10.1007/s00500-019-04286-8
    [27] H. Lai, D. Zhang, Fuzzy preorder and fuzzy topology, Fuzzy Set. Syst., 157 (2006), 1865–1885. http://dx.doi.org/10.1016/j.fss.2006.02.013 doi: 10.1016/j.fss.2006.02.013
    [28] S. Lin, J. Zhang, C. Qiu, Asymptotic analysis for one-stage stochastic linear complementarity problems and applications, Mathematics, 11 (2023), 482. http://dx.doi.org/10.3390/math11020482 doi: 10.3390/math11020482
    [29] I. Masmali, A. Ahmad, M. Azeem, A. Koam, MADM and assessment of pilot health projects based on spherical fuzzy information, Neural Comput. Applic., 35 (2023), 16619–16632. http://dx.doi.org/10.1007/s00521-023-08533-w doi: 10.1007/s00521-023-08533-w
    [30] J. Mordeson, S. Mathew, Advanced topics in fuzzy graph theory, Cham: Springer, 2019. http://dx.doi.org/10.1007/978-3-030-04215-8
    [31] Z. Mufti, A. Tabraiz, Q. Xin, B. Almutairi, R. Anjum, Fuzzy topological analysis of pizza graph, AIMS Mathematics, 8 (2023), 12841–12856. http://dx.doi.org/10.3934/math.2023647
    [32] D. Nithyanandham, F. Augustin, S. Narayanamoorthy, A. Ahmadian, D. Balaenu, D. Kang, Bipolar intuitionistic fuzzy graph based decision-making model to identify flood vulnerable region, Environ. Sci. Pollut. Res., 30 (2023), 125254–125274. http://dx.doi.org/10.1007/s11356-023-27548-3 doi: 10.1007/s11356-023-27548-3
    [33] N. Papageorgiou, Fuzzy topology and fuzzy multifunctions, J. Math. Anal. Appl., 109 (1985), 397–425. http://dx.doi.org/10.1016/0022-247X(85)90159-3 doi: 10.1016/0022-247X(85)90159-3
    [34] R. Parvathi, M. Karunambigai, Intuitionistic fuzzy graphs, In: Computational intelligence, theory and applications, Berlin: Springer, 2006,139–150. http://dx.doi.org/10.1007/3-540-34783-6_15
    [35] R. Parvathi, M. Karunambigai, K. Atanassov, Operations on intuitionistic fuzzy graphs, Proceedings of IEEE International Conference on Fuzzy Systems, 2009, 1396–1401. http://dx.doi.org/10.1109/FUZZY.2009.5277067
    [36] G. Pasi, R. Yager, K. Atanassov, Intuitionistic fuzzy graph interpretations of multi-person multi-criteria decision making: generalized net approach, Proceedings of 2nd International IEEE Conference on Intelligent Systems, 2004,434–439. http://dx.doi.org/10.1109/IS.2004.1344787
    [37] A. Rosenfeld, Fuzzy graphs, Proceedings of Fuzzy Sets and their Applications to Cognitive and Decision Processes, 1975, 77–95. http://dx.doi.org/10.1016/B978-0-12-775260-0.50008-6
    [38] J. Wang, Y. Li, Y. Wu, Z. Liu, K. Chen, C. Chen, Fixed-time formation control for uncertain nonlinear multi-agent systems with time-varying actuator failures, IEEE T. Fuzzy Syst., 32 (2024), 1965–1977. http://dx.doi.org/10.1109/TFUZZ.2023.3342282 doi: 10.1109/TFUZZ.2023.3342282
    [39] J. Wang, Y. Wu, C. Chen, Z. Liu, W. Wu, Adaptive pi event-triggered control for mimo nonlinear systems with input delay, Inform. Sciences, 677 (2024), 120817. http://dx.doi.org/10.1016/j.ins.2024.120817 doi: 10.1016/j.ins.2024.120817
    [40] Z. Wang, F. Parastesh, H. Natiq, J. Li, X. Xi, M. Mehrabbeik, Synchronization patterns in a network of diffusively delay-coupled memristive chialvo neuron map, Phys. Lett. A, 514–515 (2024), 129607. http://dx.doi.org/10.1016/j.physleta.2024.129607 doi: 10.1016/j.physleta.2024.129607
    [41] X. Wu, N. Zhou, Y. Chen, J. Sun, L. Lu, Q. Chen, et al., Lens-free on-chip 3D microscopy based on wavelength-scanning fourier ptychographic diffraction tomography, Light Sci. Appl., 13 (2024), 237. http://dx.doi.org/10.1038/s41377-024-01568-1 doi: 10.1038/s41377-024-01568-1
    [42] X. Xi, J. Li, Z. Wang, H. Tian, R. Yang, The effect of high-order interactions on the functional brain networks of boys with adhd, Eur. Phys. J. Spec. Top., 233 (2024), 817–829. http://dx.doi.org/10.1140/epjs/s11734-024-01161-y doi: 10.1140/epjs/s11734-024-01161-y
    [43] L. Zadeh, Fuzzy sets, Information and Control, 8 (1965), 338–353. http://dx.doi.org/10.1016/S0019-9958(65)90241-X
    [44] L. Zadeh, The concept of a linguistic variable and its application to approximate reasoning–-i, Inform. Sciences, 8 (1975), 199–249. http://dx.doi.org/10.1016/0020-0255(75)90036-5 doi: 10.1016/0020-0255(75)90036-5
    [45] I. Zorlutuna, S. Atmaca, Fuzzy parametrized fuzzy soft topology, NTMSCI, 4 (2016), 142–152. http://dx.doi.org/10.20852/ntmsci.2016115658 doi: 10.20852/ntmsci.2016115658
  • Reader Comments
  • © 2024 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Metrics

Article views(263) PDF downloads(36) Cited by(0)

Article outline

Figures and Tables

Figures(5)  /  Tables(12)

Other Articles By Authors

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog