A tags' arrival rate estimation method using weighted grey model(1, 1) and sliding window in mobile radio frequency identification systems. (October 2020)

• Record Type: Journal Article
• Authors: Zhang, Liqian; Fu, Xueliang; Li, Honghui
• Is Part Of: International journal of distributed sensor networks. Volume 16:Number 10(2020)
• Publication Date: 2020-10
• Subjects: Mobile radio frequency identification system -- weighted grey model -- tags' arrival rate -- slide window; Sensor networks -- Periodicals; Intelligent agents (Computer software) -- Periodicals; Multisensor data fusion -- Periodicals; 681.2
• DOI: 10.1177/1550147720967894
• Languages: English
• ISSNs: 1550-1329

Abstract

In order to guarantee the tag identification accuracy and efficiency in mobile radio frequency identification system, it is necessary to estimate the tags' arrival rate before performing identification. This research aims to develop a novel estimation method based on improved grey model(1, 1) and sliding window mechanism. By establishing tags' dynamic arrival model, this article emphasizes the importance of tags' arrival rate estimation in mobile radio frequency identification system. Using sliding window mechanism and weighted coefficients method, weighted grey model(1, 1) with sliding window (WGMSW(1, 1)) is proposed based on traditional grey model(1, 1). For experimental verification, three kinds of data are used as original data in WGMSW(1, 1). The experimental results show that the proposed method has lower estimation error rate, lower computation complexity, and high system stability.