RFID Data Analysis and Evaluation Based on Big Data and Data Clustering.
Journal
Computational intelligence and neuroscience
ISSN: 1687-5273
Titre abrégé: Comput Intell Neurosci
Pays: United States
ID NLM: 101279357
Informations de publication
Date de publication:
2022
2022
Historique:
received:
30
01
2022
accepted:
02
03
2022
entrez:
5
4
2022
pubmed:
6
4
2022
medline:
7
4
2022
Statut:
epublish
Résumé
The era people live in is the era of big data, and massive data carry a large amount of information. This study aims to analyze RFID data based on big data and clustering algorithms. In this study, a RFID data extraction technology based on joint Kalman filter fusion is proposed. In the system, the proposed data extraction technology can effectively read RFID tags. The data are recorded, and the KM-KL clustering algorithm is proposed for RFID data, which combines the advantages of the K-means algorithm. The improved KM-KL clustering algorithm can effectively analyze and evaluate RFID data. The experimental results of this study prove that the recognition error rate of the RFID data extraction technology based on the joint Kalman filter fusion is only 2.7%. The improved KM-KL clustering algorithm also has better performance than the traditional algorithm.
Identifiants
pubmed: 35378806
doi: 10.1155/2022/3432688
pmc: PMC8976611
doi:
Types de publication
Journal Article
Retracted Publication
Langues
eng
Sous-ensembles de citation
IM
Pagination
3432688Commentaires et corrections
Type : RetractionIn
Informations de copyright
Copyright © 2022 Lihua Lv.
Déclaration de conflit d'intérêts
The authors declare no conflicts of interest.
Références
AIDS. 2020 Feb 1;34(2):227-236
pubmed: 31634185
Clin Rheumatol. 2021 May;40(5):1835-1842
pubmed: 33128654
BMC Genomics. 2020 Nov 2;21(1):755
pubmed: 33138786