LAPSE:2019.0543
Published Article
LAPSE:2019.0543
Application of Data Mining in an Intelligent Early Warning System for Rock Bursts
Xuejun Zhu, Xiaona Jin, Dongdong Jia, Naiwei Sun, Pu Wang
May 16, 2019
In view of rock burst accidents frequently occurring, a basic framework for an intelligent early warning system for rock bursts (IEWSRB) is constructed based on several big data technologies in the computer industry, including data mining, databases and data warehouses. Then, a data warehouse is modeled with regard to monitoring the data of rock bursts, and the effective application of data mining technology in this system is discussed in detail. Furthermore, we focus on the K-means clustering algorithm, and a data visualization interface based on the Browser/Server (B/S) mode is developed, which is mainly based on the Java language, supplemented by Cascading Style Sheets (CSS), JavaScript and HyperText Markup Language (HTML), with Tomcat, as the server and Mysql as the JavaWeb project of the rock burst monitoring data warehouse. The application of data mining technology in IEWSRB can improve the existing rock burst monitoring system and enhance the prediction. It can also realize real-time queries and the analysis of monitoring data through browsers, which is very convenient. Hence, it can make important contributions to the safe and efficient production of coal mines and the sustainable development of the coal economy.
Keywords
clustering analysis, data mining, data warehouse, intelligent early warning, rock burst
Suggested Citation
Zhu X, Jin X, Jia D, Sun N, Wang P. Application of Data Mining in an Intelligent Early Warning System for Rock Bursts. (2019). LAPSE:2019.0543
Author Affiliations
Zhu X: State Key Laboratory of Mine Disaster Prevention and Control, Shandong University of Science and Technology, Qingdao 266590, China; National Engineering Laboratory for Coalmine Backfilling Mining, Shandong University of Science and Technology, Tai’an 27
Jin X: State Key Laboratory of Mine Disaster Prevention and Control, Shandong University of Science and Technology, Qingdao 266590, China
Jia D: State Key Laboratory of Mine Disaster Prevention and Control, Shandong University of Science and Technology, Qingdao 266590, China
Sun N: State Key Laboratory of Mine Disaster Prevention and Control, Shandong University of Science and Technology, Qingdao 266590, China
Wang P: State Key Laboratory of Mine Disaster Prevention and Control, Shandong University of Science and Technology, Qingdao 266590, China; National Engineering Laboratory for Coalmine Backfilling Mining, Shandong University of Science and Technology, Tai’an 27
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Journal Name
Processes
Volume
7
Issue
2
Article Number
E55
Year
2019
Publication Date
2019-01-22
Published Version
ISSN
2227-9717
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Original Submission
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PII: pr7020055, Publication Type: Journal Article
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LAPSE:2019.0543
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doi:10.3390/pr7020055
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May 16, 2019
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CC BY 4.0
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May 16, 2019
 
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May 16, 2019
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Original Submitter
Calvin Tsay
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