DocumentCode :
2514551
Title :
An effective method for RFID tag antenna optimization based on artifical neural network
Author :
Shang, Jiachuan ; Zhang, Ning ; Li, Xiuping
Author_Institution :
Key Lab. of Universal Wireless Commun., Beijing Univ. of Posts & Telecommun., Beijing, China
fYear :
2010
fDate :
28-30 Nov. 2010
Firstpage :
383
Lastpage :
386
Abstract :
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.
Keywords :
C++ language; antennas; electrical engineering computing; genetic algorithms; neural nets; particle swarm optimisation; radiofrequency identification; C++; RFID tag antenna optimization; artificial neural network; electromagnetic simulator; evolutionary algorithms; genetic algorithm; nonlinear model; particle swarm optimization; Artificial neural networks; Dipole antennas; Gallium; Numerical models; Optimization; Radiofrequency identification; Genetic Algorithm; Neural Network; Optimization; Particle Swarm Optimization Algorithm; Tag Antennas;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Computing and Telecommunications (YC-ICT), 2010 IEEE Youth Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-8883-4
Type :
conf
DOI :
10.1109/YCICT.2010.5713125
Filename :
5713125
Link To Document :
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