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作 者:彭华[1,2] 王用鑫[1,2] Peng Hua;Wang Yongxin(Chongqing University,Chongqing 400044,China;Chongqing College of Electronic Engineering,Chongqing 400044,China)
机构地区:[1]重庆大学,重庆400044 [2]重庆电子工程职业学院,重庆400044
出 处:《科技通报》2016年第12期184-187,共4页Bulletin of Science and Technology
基 金:重庆市教委科学技术研究项目(KJ1503010)
摘 要:如何能够让RFID阅读器进行更好的覆盖而提高信息传输的准确性一直以来都是研究的方向,本文将RFID阅读器个体与PSO中粒子进行对应,首先将RFID网络中的信号干扰,读写器分布密度和数据传输负载作为优化目标,建立优化函数。其次针对PSO算法的不足同时引入蒙特卡罗模拟和反向学习策略,使得PSO算法粒子跳出局部最优,提高算法的效率,最后仿真实验表明本文算法与QPSO在信号干扰,读写器分布密度和数据传输负载方面有了明显的提高,能够有效的提高RFID网络部署的效率。How to make the RFID reader to have better coverage and improve the accuracy of information transmission has always been the research direction. In this paper, the RFID reader individual corresponds with particles in the PSO. Firstly, interfere with signals in the RFID network and regard reader’s distribution density and data transmission load as the optimization goal to establish the optimization function. Secondly, aiming at the deficiency of the PSO algorithm, introduce the Monte Carlo simulation and reverse learning strategy to enable the PSO algorithm particle to get out of the local optimization and improve the algorithm’s efficiency. Finally, the simulation experiment shows that algorithm in this paper and QPSO have been significantly improved in terms of reader’s distribution density and data transmission load, which can effectively improve the efficiency of RFID network optimization.
分 类 号:TP393[自动化与计算机技术—计算机应用技术]
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