基于BSO-BP改进动态帧时隙算法的密集环境下RFID标签读写优化方法OACSTPCD

Wireless radio frequency identification technology,as a key technology of the Internet of Things,is constantly developing and widely applied in the manufacturing industry of China.In order to solve the data collision phenomenon caused by the competition of channels during the reading and writing of a large number of wireless radio frequency identification tags,accurate estimation of the number of tags is required.On the basis of the traditional dynamic frame time slot algorithm,the Tian Niu swarm search algorithm is used to find the optimal initial weight and threshold of the BP neural network,and the optimal value is used to the parameter set of BP neural network,achieving accurate estimation of the number of labels.The production effect of RFID(radio frequency identification)bound power cords by experiments and actual use by enterprises proves that,in combination with the traditional dynamic frame time slot algorithm,the proposed improved algorithm can not only ensure the accuracy of reading,but also shorten the reading time,effectively improving the efficiency of the system.