• Journal of Terahertz Science and Electronic Information Technology
  • Vol. 19, Issue 5, 946 (2021)
TANG Yangkun* and CUI Yinghua
Author Affiliations
  • [in Chinese]
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    DOI: 10.11805/tkyda2020296 Cite this Article
    TANG Yangkun, CUI Yinghua. RFID localization based on differential evolution algorithm[J]. Journal of Terahertz Science and Electronic Information Technology , 2021, 19(5): 946 Copy Citation Text show less
    References

    [1] BILODEAU J S,BOUZOUANE A,BOUCHARD B,et al. An experimental comparative study of RSSI-based positioning algorithms for passive RFID localization in smart environments[J]. Journal of Ambient Intelligence & Humanized Computing, 2017,9(5):1327-1343.

    [2] WANG Zimin,HE Baiqing. RFID location algorithm[J]. MATEC Web of Conferences, 2016(63):1-5.

    [3] NI L M,LIU Y H. LANDMARC:indoor location sensing using active RFID[J]. Wireless Networks, 2004,10(6):701-710.

    [4] HAN K,CHO S H. Advanced LANDMARC with adaptive k-nearest algorithm for RFID location system[C]//IEEE International Conference on Network Infrastructure & Digital Content. Beijing,China:IEEE, 2010:595-598.

    [7] ANNEPU V,RAJESH A. Implementation of self-adaptive mutation factor and cross-over probability based differential evolution algorithm for node localization in wireless sensor networks(Article)[J]. Evolutionary Intelligence, 2019,12(3): 469-478.

    [9] LIN Meijin,WANG Zhenyu,WANG Fei. Hybrid differential evolution and particle swarm optimization algorithm based on random inertia weight[C]//2019 34th Youth Academic Annual Conference of Chinese Association of Automation(YAC). Jinzhou,China:[s.n.], 2019:411-414.

    [10] WANG Shihao,LI Yuzhen,YANG Hongyu. Self-adaptive mutation differential evolution algorithm based on particle swarm optimization[J]. Applied Soft Computing Journal, 2019(81):1-22.

    TANG Yangkun, CUI Yinghua. RFID localization based on differential evolution algorithm[J]. Journal of Terahertz Science and Electronic Information Technology , 2021, 19(5): 946
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