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2018 13th IEEE Conference on Industrial Electronics and Applications (ICIEA)
In the experiments, we compare the improved distributed parallel particle swarm optimization (IDPPSO) algorithm with the PCCPSO algorithm, and make Wilcoxon test on the results. ... To solve the high-dimensional RFID reader-to-reader collision problem effectively, we improve the parallel cooperative co-evolution particle swarm optimization (PCCPSO) algorithm by adopting the hybrid ... IMPROVED DISTRIBUTED PARALLEL PSO ALGORITHM BASED ON MPI A. ...doi:10.1109/iciea.2018.8397901 fatcat:sbvhifqz4jbsti5mwhb7xpwxfy
In this work, simulation annealing based anti-collision protocol is proposed where there is uniform distribution of channels among readers. ... Majority of probabilistic and deterministic anticollisions methods are inefficient in channel distribution and improving the performance. ... Next, the particle swarm optimization algorithms are easy to fall into local optimum in highly dense network, thus do not provide global optimum solution. Tao et al. ...doi:10.24138/jcomss.v12i4.75 fatcat:qkkboi4irzhdlh7wx5sqxgwwdy
The article titled "RFID reader anticollision based on distributed parallel particle swarm optimization" addresses the problem of collisions when a large number of RFID readers are deployed and proposes ... a distributed parallel cooperative co-evolution approach to produce a complex optimization for collision prevention. ...doi:10.1109/jiot.2021.3053713 fatcat:wnsgkuohhvg4fitk6ixreddsly
This paper presents a survey of recent research in BIAs, which focuses on the research in the realization of various BIAs based on different working mechanisms and the applications for mobile robot control ... a development bottleneck in this field, such as complex computing and the dependence on high-precision sensors. ...  proposed an artificial immune network based anticollision algorithm for dense RFID readers, where the major immune operators are designed to satisfy the practical convention of RFID systems, and ...doi:10.1155/2016/3810903 pmid:26819582 pmcid:PMC4707020 fatcat:xq4zktll3ja6be6veraqgws5zm