NDLI: RFID reader deployment using RBFNN with L-GEM

Content Provider	IEEE Xplore Digital Library
Author	Hai-Lan Ding Ng, W.W.Y. Chan, P.P.K. Yeung, D.S. Dong-Liang Wu
Copyright Year	2010
Description	Author affiliation: Machine Learning and Cybernetics Research Center, School of Computer Science and Engineering, South China, University of Technology, Guangzhou 511400, China (Hai-Lan Ding; Ng, W.W.Y.; Chan, P.P.K.; Yeung, D.S.; Dong-Liang Wu)
Abstract	RFID technology has been deployed in a wide range of industries. The deployment of RFID readers is essential to the success of RFID applications. RFID is a wireless communication technology and therefore the interaction between the RFID tag and reader is easily influenced by many factors. Current RFID reader deployment based on designer experience or predefined mathematical model without field test. When the RFID system is fielded, the performance may be unsatisfactory. Therefore, we propose a neural network based method to select the best location of RFID reader deployment among possible choices in the field. The major factor affecting the performance of neural network is the architecture selection which we will select via a minimization of its localized generalization error to enhance the neural network's generalization capability. Radial basis function neural network is adapted owing to its fast learning speed. The neural network will suggest the best location iteratively to reduce the number of cost and labor intensive random trials. Experimental results on an artificial warehouse show that the proposed method outperforms random trials.
Starting Page	1153
Ending Page	1158
File Size	195175
Page Count	6
File Format	PDF
ISBN	9781424465262
e-ISBN	9781424465279
DOI	10.1109/ICMLC.2010.5580926
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-07-11
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Radiofrequency identification Training Neurons Artificial neural networks Machine learning Cybernetics Mathematical model RBFNN RFID reader deployment L-GEM
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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