[1] Meng Fanrong, Zhou Yong, Xia Shixiong,. Clustering analysis algorithm for security supervising databased on semantic description in coal mines [J]. Journal of Southeast University (English Edition), 2008, 24 (3): 354-357. [doi:10.3969/j.issn.1003-7985.2008.03.025]

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Clustering analysis algorithm for security supervising databased on semantic description in coal mines()

基于语义描述的煤矿安全监测数据聚类分析算法

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Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]

Volumn:

24

Issue:

2008 3

Page:

354-357

Research Field:

Automation

Publishing date:

2008-09-30

Info

Title:

Clustering analysis algorithm for security supervising databased on semantic description in coal mines

基于语义描述的煤矿安全监测数据聚类分析算法

Author(s):

Meng Fanrong;  Zhou Yong;  Xia Shixiong

School of Computer Science and Technology, China University of Mining and Technology, Xuzhou 221116, China

孟凡荣;  周勇;  夏士雄

中国矿业大学计算机科学与技术学院, 徐州 221116

Keywords:

semantic description;  clustering analysis algorithm;  similarity measurement

语义描述;  聚类分析算法;  相似性度量

PACS:

TP18

DOI:

10.3969/j.issn.1003-7985.2008.03.025

Abstract:

In order to mine production and security information from security supervising data and to ensure security and safety involved in production and decision-making, a clustering analysis algorithm for security supervising data based on a semantic description in coal mines is studied.First, the semantic and numerical-based hybrid description method of security supervising data in coal mines is described.Secondly, the similarity measurement method of semantic and numerical data are separately given and a weight-based hybrid similarity measurement method for the security supervising data based on a semantic description in coal mines is presented.Thirdly, taking the hybrid similarity measurement method as the distance criteria and using a grid methodology for reference, an improved CURE clustering algorithm based on the grid is presented.Finally, the simulation results of a security supervising data set in coal mines validate the efficiency of the algorithm.

为了挖掘基于语义描述的煤矿安全监测数据中蕴含的生产安全信息, 指导煤矿安全生产和决策, 研究了基于语义描述的煤矿安全监测数据聚类分析算法.首先, 阐述了煤矿安全监测数据的语义和数值混合描述方法;接着, 分别给出了语义和数值数据的相似性度量方法, 以及基于权重的煤矿安全监测数据的混合相似性度量方法;然后, 以混合相似性度量方法为距离度量准则, 并借鉴网格的思想, 给出了基于网格的改进CURE聚类算法.通过煤矿安全监测数据集的仿真实验, 验证了所提算法的有效性.

References:

[1] Zhou Yong, Xia Shixiong.A hybrid similarity measurement for complicated and multi-source data in coal mine [J].Journal of Jiangnan University:Natural Science Edition, 2007, 6(6):665-668.(in Chinese)
[2] Alexander M, Steffen S.Measuring similarity between ontologies [C]//Proceedings of the 13th International Conference on Knowledge Engineering and Knowledge Management.Springer-Verlag, 2003:251-263.
[3] Resnik P.Using information content to evaluate semantic similarity in taxonomy [C]//Proceedings of the International Joint Conference on Artificial 14th Intelligence.Montreal, Canada, 1995:445-453.
[4] Lin D.An information-theoretic definition of similarity [C]//Fifteenth International Conference on Machine Learning (ICML’98).Madison, Wisconsin, 1998:296-304.
[5] Cao Hongqi, Yu Lan, Sun Zhihui.An algorithm of outliers mining based on grid clustering techniques[J].Computer Engineering, 2006, 32(11):119-121.(in Chinese)
[6] Yang Yanguo, Ti Zhengyi.Research on fuzzy comprehensive evaluation method of mine coal and gas outburst hazard [J].Express Information of Mining Industry, 2006, 32(8):33-36.(in Chinese)

Memo

Memo:

Biography: Meng Fanrong(1962—), female, doctor, associate professor, mengfr62@163.com.
Foundation items: The National Natural Science Foundation of China(No.50674086), Specialized Research Fund for the Doctoral Program of Higher Education(No.20060290508), the Postdoctoral Scientific Program of Jiangsu Province(No.0701045B).
Citation: Meng Fanrong, Zhou Yong, Xia Shixiong.Clustering analysis algorithm for security supervising data based on semantic description in coal mines[J].Journal of Southeast University(English Edition), 2008, 24(3):354-357.

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