【摘要】：RFID以其掃描快、體積小、形式多、穿透力強(qiáng)及安全性好等特點(diǎn)被廣泛運(yùn)用于物流供應(yīng)鏈系統(tǒng)、生產(chǎn)制造行業(yè)、交通運(yùn)輸管理等。帶有RFID標(biāo)簽的物品在移動(dòng)過程中會(huì)產(chǎn)生大量的RFID路徑數(shù)據(jù),如何從中提取有用的信息和知識(shí),已經(jīng)成為目前研究的重點(diǎn)。 本文詳細(xì)的介紹了RFID技術(shù)及其原理,并且結(jié)合RFID農(nóng)產(chǎn)品追溯系統(tǒng),分析了RFID路徑數(shù)據(jù)特點(diǎn),設(shè)計(jì)并且實(shí)現(xiàn)RFID技術(shù)在農(nóng)產(chǎn)品追溯系統(tǒng)各個(gè)環(huán)節(jié)中的應(yīng)用。由于射頻識(shí)別技術(shù)容易受到外界環(huán)境的影響,導(dǎo)致RFID閱讀器的準(zhǔn)確率較低,造成了數(shù)據(jù)的不確定性,需要在數(shù)據(jù)存儲(chǔ)之前對(duì)RFID數(shù)據(jù)進(jìn)行預(yù)處理。 針對(duì)自適應(yīng)滑動(dòng)窗口清洗算法SMURF(Statistical sMoothing for Unreliable RFid data),本文提出基于動(dòng)態(tài)標(biāo)簽的RFID不確定性數(shù)據(jù)清洗算法DSMURF(Dynamic tags-based SMURF),通過構(gòu)建真實(shí)的實(shí)驗(yàn)平臺(tái)來分析閱讀器準(zhǔn)確率與標(biāo)簽距離、天線角度、標(biāo)簽速度之間的關(guān)系。自適應(yīng)滑動(dòng)窗口算法SMURF對(duì)于動(dòng)態(tài)標(biāo)簽窗口設(shè)置過大,導(dǎo)致讀取值與實(shí)際值之間存在較大誤差。DSMURF算法通過設(shè)定標(biāo)簽的速度、閱讀器的時(shí)隙、閱讀器的閱讀范圍來構(gòu)建滑動(dòng)窗口的大小。此外,SMURF算法沒有對(duì)冗余數(shù)據(jù)進(jìn)行處理,本文提出了RFID數(shù)據(jù)冗余清洗框架,有效地降低了數(shù)據(jù)的冗余量,并通過實(shí)驗(yàn)平臺(tái)和仿真數(shù)據(jù)集驗(yàn)證DSMURF算法的性能。 本文提出基于在線微聚類和離線宏聚類的RFID數(shù)據(jù)流聚類算法RCluStream。路徑對(duì)象的相似性度量是聚類分析的基礎(chǔ),首先提出RFID路徑數(shù)據(jù)相似性定義。RFID路徑數(shù)據(jù)具有流的特征,在聚類過程中,簇會(huì)因?yàn)閿?shù)據(jù)的流入而不斷地發(fā)生變化。在線微聚類設(shè)立簇的聚類特征,當(dāng)簇發(fā)生改變時(shí),記錄簇的聚類特征；同時(shí),離線宏聚類可以根據(jù)用戶輸入的時(shí)間參數(shù),通過返回簇的聚類特征,獲得這段時(shí)間簇的變化情況,從而有利于決策和分析。最后,開發(fā)了RFID農(nóng)產(chǎn)品追溯系統(tǒng)和信息處理系統(tǒng),將路徑數(shù)據(jù)可視化,直觀地表現(xiàn)路徑數(shù)據(jù)的分布和挖掘結(jié)果,實(shí)驗(yàn)表明RCluStream算法的有效性。
[Abstract]:RFID is widely used in logistics supply chain system, manufacturing industry, transportation management and so on because of its fast scanning, small size, many forms, strong penetration and good security. RFID tagged goods will produce a large number of RFID path data in the process of moving. How to extract useful information and knowledge from it has become the current research. The focus of the study.
This paper introduces RFID technology and its principle in detail, and combines with RFID traceability system for agricultural products, analyzes the characteristics of RFID path data, designs and implements the application of RFID technology in every link of agricultural products traceability system. The uncertainty of data requires pre processing of RFID data before data storage.
Aiming at SMURF (Statistical Moothing for Unreliable RFid data), this paper proposes a dynamic tags-based algorithm DSMURF (Dynamic tags-based SMURF) for RFID uncertain data cleaning, which analyzes the accuracy of the reader and tag distance, antenna angle and tag speed by constructing a real experimental platform. The size of the sliding window is constructed by setting the speed of the tag, the time slot of the reader and the reading range of the reader. In addition, the SMURF algorithm does not process the redundant data. In this paper, a redundancy cleaning framework for RFID data is proposed, which effectively reduces the redundancy of data. The performance of DSMURF algorithm is verified by experimental platform and simulation data sets.
In this paper, we propose an RFID data stream clustering algorithm RCluStream based on on-line micro-clustering and off-line macro-clustering. The similarity measure of path objects is the basis of clustering analysis. Firstly, the similarity definition of RFID path data is proposed. Linear micro-clustering sets up clustering features and records clustering features when the clusters change. At the same time, off-line macro-clustering can get the changes of the clusters by returning the clustering features of the clusters according to the time parameters input by users, which is beneficial to decision-making and analysis. Finally, RFID agricultural products traceability system and information are developed. The processing system visualizes the path data and visualizes the distribution and mining results of the path data. Experiments show that the RCluStream algorithm is effective.
【學(xué)位授予單位】：浙江工業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TP391.44

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