Radio frequency identification (RFID) is a kind of automatic identification technology which can be used for indoor positioning system. In this paper, an indoor RFID location algorithm is proposed based on nonlinear support vector regression (SVR) and particle swarm optimization (PSO). The algorithm uses SVR to construct the nonlinear mapping relation between received signal strength indication (RSSI) and distance between the tags and the readers. Based on nonlinear mapping relation, the nonlinear equation set is constructed. In addition, through applying PSO to optimize the objective function converted by nonlinear equation set, the coordinate position of target tag can be estimated. Finally, the simulation of this algorithm and some other algorithms is conducted. The experimental results show that SVR-PSO algorithm is more efficient than the previous algorithms in terms of positioning accuracy and positioning stability.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    An Indoor RFID Location Algorithm Based on Support Vector Regression and Particle Swarm Optimization


    Beteiligte:
    Yang, Li (Autor:in) / Liu, Qinshu (Autor:in) / Xu, Jie (Autor:in) / Hu, Jing (Autor:in) / Song, Tiecheng (Autor:in)


    Erscheinungsdatum :

    01.08.2018


    Format / Umfang :

    676405 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Online Support Vector Regression Predictive Control Algorithm Based on Particle Swarm Optimization

    Chen, Jindong / Pan, Feng | British Library Online Contents | 2013


    RFID Network Scheduling Based on Symbiotic Particle Swarm Optimization

    Gao, Z. / Pang, H. / Wang, D. et al. | British Library Online Contents | 2012



    Particle Swarm Optimization Algorithm

    Chen, G.-c. / Yu, J.-s. | British Library Online Contents | 2005