AN EFFECTIVE METHOD FOR RFID TAG ANTENNA OPTIMIZATION BASED ON ARTIFICAL NEURAL NETWORK
Evolutionary algorithms combined with artificial neural network (ANN) have been applied in RFID tag antenna optimization platform. An effective method for RFID tag antenna optimization by particle swarm optimization (PSO) algorithm or genetic algorithm (GA) combined with ANN is presented in this paper. ANN is used to establish the non-linear model of tag antenna which is shown to be as accurate as an electromagnetic simulator and can be used for constructing the fitness function of PSO and GA. The PSO and GA optimizers are developed and executed in C++. Finally, this optimization method is turned out to be much more efficient than any electromagnetic simulator optimization. In addition, the PSO optimization results show that it is faster than GA.
Optimization Tag Antennas Particle Swarm Optimization Algorithm Genetic Algorithm Neural Network
Jiachuan Shang Ning Zhang Xiuping Li
Key Laboratory of Universal Wireless Communications, Ministry of Education Beijing University of Posts and Telecommunications, Beijing, China State Key Laboratory of Millimeter Waves, 210096, Nanjing
国际会议
2010 IEEE Youth Conference on Information,Computing and Telecommunications(2010 IEEE青年信息、计算和通信技术大会)
北京
英文
383-386
2010-11-28（万方平台首次上网日期，不代表论文的发表时间）