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ĐÁNH GIÁ HIỆU QUẢ QUY HOẠCH MẠNG RFID

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jos.hueuni.edu.vn Tập 133, Số 2A, 2024 43 Tài liệu tham khảo 1. X. Jia, Q. Feng, T. Fan, and Q. Lei, “RFID technology and its applications in Internet of Things (IoT),” 2012 2nd Int. Conf. Consum. Electron. Commun. Networks, CECNet 2012 - Proc., pp. 1282–1285, 2012, doi: 10.1109/CECNet.2012.6201508. 2. F. Costa, S. Genovesi, M. Borgese, A. Michel, F. A. Dicandia, and G. Manara, “A review of rfid sensors, the new frontier of internet of things,” Sensors, vol. 21, no. 9, 2021, doi: 10.3390/s21093138. 3. Q. Guan, Y. Liu, Y. Yang, and W. Yu, “Genetic Approach for Network Planning in the RFID Systems,” in Sixth International Conference on Intelligent Systems Design and Applications, Oct. 2006, vol. 2, pp. 567–572. doi: 10.1109/ISDA.2006.253899. 4. D. Karaboga and B. Akay, “Artificial Bee Colony (ABC) Algorithm on Training Artificial Neural Networks,” in 2007 IEEE 15th Signal Processing and Communications Applications, IEEE, Jun. 2007, pp. 1–4. doi: 10.1109/SIU.2007.4298679. 5. H. Chen, Y. Zhu, L. Ma, and B. Niu, “Multiobjective RFID network optimization using multiobjective evolutionary and swarm intelligence approaches,” Math Probl Eng, vol. 2014, 2014, doi: 10.1155/2014/961412. 6. N. Bacanin, M. Tuba, and I. Strumberger, “RFID Network Planning by ABC Algorithm Hybridized with Heuristic for Initial Number and Locations of Readers,” in Proceedings - UKSim-AMSS 17th International Conference on Computer Modelling and Simulation, UKSim 2015, Institute of Electrical and Electronics Engineers Inc., Sep. 2016, pp. 39–44. doi: 10.1109/UKSim.2015.83.

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7. S. Jing, X. Lian, H. Chen, T. Zou, and L. Ma, “Optimal layout and deployment for RFID system using a novel hybrid artificial bee colony optimizer based on bee life-cycle model,” Soft comput, vol. 21, no. 14, pp. 4055–4083, Jul. 2017, doi: 10.1007/s00500-016-2056-7. 8. L. Ma, X. Wang, M. Huang, Z. Lin, L. Tian, and H. Chen, “Two-Level Master–Slave RFID Networks Planning via Hybrid Multiobjective Artificial Bee Colony Optimizer,” IEEE Trans Syst Man Cybern Syst, vol. 49, no. 5, pp. 861–880, May 2019, doi: 10.1109/TSMC.2017.2723483. 9. X.-S. Yang and Suash Deb, “Cuckoo Search via Lévy flights,” in 2009 World Congress on Nature & Biologically Inspired Computing (NaBIC), IEEE, Mar. 2009, pp. 210–214. doi: 10.1109/NABIC.2009.5393690. 10. A. Jaballah and A. Meddeb, “A new variant of cuckoo search algorithm with self adaptive parameters to solve complex RFID network planning problem,” Wireless Networks, vol. 25, no. 4, pp. 1585–1604, May 2019, doi: 10.1007/s11276-017-1616-9. 11. A. Nawawi et al., “Comparative evaluation of the gradient-based cuckoo search (GBCS) and (MC- GPSO) techniques for optimal RFID network planning ,” International Journal of Mechanical Engineering and Technology (IJMET), vol. 10, no. 01, pp. 677–689, 2019. 12. K. Hasnan, N. H. Talib, and A. Nawawi, “Analysis of gradient-based cuckoo search for the large scale optimal rfid network planning,” in Journal of Physics: Conference Series, Institute of Physics Publishing, Mar. 2019. doi: 10.1088/1742-6596/1150/1/012008.

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13. X. S. Yang, “Firefly algorithms for multimodal optimization,” in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2009, pp. 169–178. doi: 10.1007/978-3-642-04944-6_14.