Monitoring of flooding water under coal mine based on improved fuzzy clustering

被引:0
|
作者
Nie, Mengya [1 ]
Zhou, Mengran [1 ]
Fu, Xueqiang [1 ]
机构
[1] Anhui Univ Sci & Technol, Dept Elect Engn, Huainan, Peoples R China
来源
ADVANCES IN CIVIL AND INDUSTRIAL ENGINEERING IV | 2014年 / 580-583卷
关键词
water quality monitoring; fuzzy clustering; FCM; PSO-FCM;
D O I
10.4028/www.scientific.net/AMM.580-583.2713
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Due to the complicated coal mine flooding water quality monitoring data, in order to extract the effective data from vast amounts of data, this article used the fuzzy clustering to analyze the monitoring data processing. This study makes a brief analysis of monitoring data structure, then analyzes the shortcomings of fuzzy C mean clustering algorithm(FCM), which also proposes fuzzy C-means algorithm based on particle swarm optimization (PSO-FCM). Finally samples of the underground water data are used to carry out the instance simulation. The experiment results showed that in dealing with data samples. The algorithm had some advantages and it was worthy of research.
引用
收藏
页码:2713 / +
页数:2
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