WIT120 data mining technology based on internet of things

被引：0
|
作者：
Qingyuan Zhou
Zongming Zhang
Yuancong Wang
机构：
[1] Changzhou Vocational Institute of Mechatronic Technology,School of Economics and Management
[2] Changzhou Vocational Institute of Mechatronic Technology,Changzhou Key Laboratory of Industrial Internet and Data Intelligence
[3] Changzhou Vocational Institute of Mechatronic Technology,Changzhou Electronic Commerce Research Institute
[4] Xidian University,School of Economics and Management
[5] The University of Texas at Dallas,Naveen Jindal School of Management
[6] Sichuan University,School of Public Administration
来源：
Health Care Management Science | 2020年 / 23卷
关键词：
Data mining; MapReduce; Solf-evolving; K-means;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
In recent years, with the increasing aging of society, the number of patients with chronic heart disease, hypertension and diabetes has increased dramatically. It has guiding significance for the prevention and treatment by long-term monitoring of the physiological signs of patients with chronic diseases, scoring statistical data, and predicting the development trend of users’ health. The work used the data collected by WIT120 system to analyze the pre-processed thick data based on adaptive k-means clustering method under the MapReduce framework, and the GM (1,1) grey model was used to predict the future health status of users. The simulation results have verified the effectiveness of the proposed algorithm.
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页码：680 / 688
页数：8
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