2836-7863ISSN (Online)
Volume 1 , Issue 1 , PP: 34-40, 2023 | Cite this article as | XML | Html | PDF | Full Length Article
Ahmed Sleem 1 * , Ibrahim Elhenawy 2
Doi: https://doi.org/10.54216/NIF.010104
In latest days, 5G technology has undergone fast development and has since found widespread use in a variety of industries including medicine, travel, agriculture, and others. The 5G network's fundamental equipment, known as 5G ground stations, are responsible for achieving wireless signal transfer among wired communications systems and wireless endpoints. Additionally, 5G stations give communication range. Nevertheless, as the size of 5G ground stations continues to progressively develop, difficulties such as inadequate coverage area and subpar user experiences commonly arise. As a result, it is essential to conduct an all-encompassing performance evaluation of 5G ground stations in order to better understand the challenges that now exist in the development of ground stations. To begin, the components of the performance assessment index system, which include operating efficiency, economic condition, ecological effects, and social pressure, are assembled from their respective vantage points. In the next step, a unique hybrid multi-criteria decision-making (MCDM) approach that is built on the AHP methodology is used. In conclusion, ten 5G base stations are selected as samples for further investigation. The AHP is integrated with the Interval Valued Neutrosophic Sets (IVNSs). The IVNSs used to overcome incomplete and vague information. The AHP method used to compute the weights of criteria.
Interval Valued Neutrosophic Sets , MCDM , 5G , AHP , Network
[1] S. K. Rao and R. Prasad, “Impact of 5G technologies on industry 4.0,” Wireless personal communications, vol. 100, pp. 145–159, 2018.
[2] M. Attaran, “The impact of 5G on the evolution of intelligent automation and industry digitization,” Journal of Ambient Intelligence and Humanized Computing, pp. 1–17, 2021.
[3] X. Peng, X. Zhang, and Z. Luo, “Pythagorean fuzzy MCDM method based on CoCoSo and CRITIC with score function for 5G industry evaluation,” Artificial Intelligence Review, vol. 53, no. 5, pp. 3813–3847, 2020.
[4] L. Wang, F. Jia, L. Chen, Q. Xu, and X. Lin, “Exploring the dependence structure among Chinese firms in the 5G industry,” Industrial Management & Data Systems, vol. 121, no. 2, pp. 409–435, 2021.
[5] D. Peraković, M. Periša, P. Zorić, and I. Cvitić, “Development and implementation possibilities of 5G in Industry 4.0,” in Advances in Design, Simulation and Manufacturing III: Proceedings of the 3rd International Conference on Design, Simulation, Manufacturing: The Innovation Exchange, DSMIE-2020, June 9-12, 2020, Kharkiv, Ukraine–Volume 1: Manufacturing and Materials Engineering, 2020, pp. 166–175.
[6] A. Aijaz, “Private 5G: The future of industrial wireless,” IEEE Industrial Electronics Magazine, vol. 14, no. 4, pp. 136–145, 2020.
[7] J. Ordonez-Lucena, J. F. Chavarria, L. M. Contreras, and A. Pastor, “The use of 5G Non-Public Networks to support Industry 4.0 scenarios,” in 2019 IEEE Conference on Standards for Communications and Networking (CSCN), 2019, pp. 1–7.
[8] I. Jovović, S. Husnjak, I. Forenbacher, and S. Maček, “Innovative application of 5G and blockchain technology in industry 4.0,” EAI Endorsed Transactions on Industrial Networks and Intelligent Systems, vol. 6, no. 18, 2019.
[9] M. Liang et al., “Evaluating the Comprehensive Performance of 5G Base Station: A Hybrid MCDM Model Based on Bayesian Best-Worst Method and DQ-GRA Technique,” Mathematical Problems in Engineering, vol. 2022, pp. 1–15, 2022.
[10] S. Chen and S. Kang, “A tutorial on 5G and the progress in China,” Frontiers of Information Technology & Electronic Engineering, vol. 19, no. 3, pp. 309–321, 2018.
[11] E. O’Connell, D. Moore, and T. Newe, “Challenges associated with implementing 5G in manufacturing,” in Telecom, 2020, vol. 1, no. 1, p. 5.
[12] M. Gundall et al., “Introduction of a 5G-enabled architecture for the realization of industry 4.0 use cases,” IEEE access, vol. 9, pp. 25508–25521, 2021.
[13] J. Peng, J. Wang, and W.-E. Yang, “A multi-valued neutrosophic qualitative flexible approach based on likelihood for multi-criteria decision-making problems,” International Journal of Systems Science, vol. 48, no. 2, pp. 425–435, 2017.
[14] P. Chellamani and D. Ajay, “Pythagorean neutrosophic Dombi fuzzy graphs with an application to MCDM,” Neutrosophic Sets and Systems, vol. 47, pp. 411–431, 2021.
[15] M. Abdel-Basset, A. Gamal, L. H. Son, and F. Smarandache, “A bipolar neutrosophic multi criteria decision making framework for professional selection,” Applied Sciences, vol. 10, no. 4, p. 1202, 2020.
[16] J. Peng, J. Wang, and X. Wu, “An extension of the ELECTRE approach with multi-valued neutrosophic information,” Neural Computing and Applications, vol. 28, pp. 1011–1022, 2017.
[17] V. Uluçay, A. Kılıç, İ. Yıldız, and M. Şahin, An outranking approach for MCDM-problems with neutrosophic multi-sets. Infinite Study, 2019.
[18] M. R. Ahmad, M. Saeed, U. Afzal, and M.-S. Yang, “A novel MCDM method based on plithogenic hypersoft sets under fuzzy neutrosophic environment,” Symmetry, vol. 12, no. 11, p. 1855, 2020.
[19] I. M. Hezam, M. K. Nayeem, A. Foul, and A. F. Alrasheedi, “COVID-19 Vaccine: A neutrosophic MCDM approach for determining the priority groups,” Results in physics, vol. 20, p. 103654, 2021.
[20] A. Kharal, “A neutrosophic multi-criteria decision making method,” New Mathematics and Natural Computation, vol. 10, no. 02, pp. 143–162, 2014.
[21] M. Abdel-Basset, M. Mohamed, and F. Smarandache, “An extension of neutrosophic AHP–SWOT analysis for strategic planning and decision-making,” Symmetry, vol. 10, no. 4, p. 116, 2018.
[22] E. Bolturk and C. Kahraman, “A novel interval-valued neutrosophic AHP with cosine similarity measure,” Soft Computing, vol. 22, no. 15, pp. 4941–4958, 2018.
[23] M. Junaid, Y. Xue, M. W. Syed, J. Z. Li, and M. Ziaullah, “A neutrosophic ahp and topsis framework for supply chain risk assessment in automotive industry of Pakistan,” Sustainability, vol. 12, no. 1, p. 154, 2019.
[24] N. M. Radwan, M. B. Senousy, and M. R. Alaa El Din, Neutrosophic AHP multi criteria decision making method applied on the selection of learning management system. Infinite Study, 2016.
[25] M. Yucesan and M. Gul, “Failure modes and effects analysis based on neutrosophic analytic hierarchy process: method and application,” Soft Computing, vol. 25, no. 16, pp. 11035–11052, 2021.
[26] I. Deli, “Interval-valued neutrosophic soft sets and its decision making,” International Journal of Machine Learning and Cybernetics, vol. 8, no. 2, pp. 665–676, 2017.
[27] H. Zhang, J. Wang, and X. Chen, “An outranking approach for multi-criteria decision-making problems with interval-valued neutrosophic sets,” Neural Computing and Applications, vol. 27, no. 3, pp. 615–627, 2016.
