电子学报2011，Vol.39Issue(3)：579-584,6.
AMUR:一种RFID数据不确定性的自适应度量算法
AMUR: An Adaptive Measuring Algorithm of Underlying Uncertainty for RFlD Data
摘要
Abstract
To adapt the character of evolving over time and real-time of sensor data in location tracing service based on RFID, we present an adaptive evolving particle filtering algorithm-AMUR(an adaptive measuring algorithm of underlying uncertainty for RFID data). AMUR adaptively changes the number of samples on the basis of K-L distance, introduces an improved PSO (particle swarm optimization) method to enhance the efficiency of resampling phase of conventional particle filter(SIRPF) .Meanwhile,to detect the most optimal samples among candidate sample set,AMUR defines a fitness function based on CWA(conventional weighted aggregation) for PSO which balances the importance between pfiori density and likelihood densitys. It provides a reliable measure of confidence for initial tuple in the probability RFID database. Experimental comparison of current algorithms shows, AMUR outpreforms current methods in terms of measurement of underlying uncertainties over RFID data, particle degradation and particle depletion.关键词
无线射频识别/物联网/不确定性/粒子滤波/自适应/粒子群优化Key words
RFID/Intemet of things/uncertainty/particle filter/adaptive/particle swarm optimization分类
信息技术与安全科学引用本文复制引用
王永利,钱江波,孙淑荣,张功萱,刘冬梅..AMUR:一种RFID数据不确定性的自适应度量算法[J].电子学报,2011,39(3):579-584,6.基金项目
国家自然科学基金项目(No.60803001,No.60803021,No.60850002) （No.60803001,No.60803021,No.60850002）
中国博士后科学基金特别资助项目(No.200902517) （No.200902517）
江苏省博士后基金(No.0801043B) （No.0801043B）
南京市科技计划项目(No.2010软资02014) （No.2010软资02014）
