Journal
NEUROCOMPUTING
Volume 123, Issue -, Pages 354-361Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.neucom.2013.07.032
Keywords
Neural network; Continuous Ant Colony Optimization; RFID technology; RFID reflected signal strength; RFID signal distribution model
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Funding
- Natural Science Foundation of China [61174094, 61273138]
- Program for New Century Excellent Talents in University of China [NCET-10-0506]
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Radio Frequency Identification (RFID) has been rapidly developing for recent years as a kind of near field wireless communication technology depending on radio frequence signal. Now there are widespread researches and applications about RFID. To make the distribution of tags' position rational and efficient, it is significant to obtain the signal strength model around reader. This paper uses neural network method to model the RFID reflected signal strength distribution. To achieve a satisfied solution, a continuous Ant Colony Optimization algorithm that can overcome the defect of BP algorithm is combined with neural network. We discuss the mechanism of algorithm in detail. The simulation and the actual experiment results are shown to prove the good performance of this method. (C) 2013 Elsevier B.V. All rights reserved.
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