基于差异双聚类挖掘的航空磁测数据分析方法
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- 英文论文题名：A New Method for Aeromagnetic Field Observation Data Analysis Based on Differential Biclustering Mining
- 论文作者：王淼 ; 张丽花 ; 王雪 ; 龚诚
- 英文论文作者：WANG Miao ; ZHANG Li-hua ; WANG Xue ; GONG Cheng ; Science and Technology on Avionics Integration Laboratory ; China National Aeronautical Radio Electronics Research Institute
- 年：2016
- 作者机构：航空电子系统综合技术重点实验室;中国航空无线电电子研究所;
- 论文关键词：差异双聚类 ; 航空地磁场观测 ; 挖掘
- 英文论文关键词：differential biclustering ; aeromagnetic field observation ; mining
- 会议召开时间：2016-07-15
- 会议录名称：2016航空试验测试技术学术交流会论文集
- 语种：中文
- 分类号：P318.63;P315.721
- 学会代码：ZGHU
- 学会名称：中国航空学会
- 页数：4
- 文件大小：381k
- 原文格式：O
摘要
航空地磁场观测相对于传统的地面地磁点测方式和电磁卫星测量方法,可以获取更大区域的地磁场数据,能从中挖掘出可能与地震前兆有关的知识。使用差异双聚类挖掘算法,从不同时期相同地磁点的航空地磁数据集中挖掘具有差异特性的双聚类,用来发现哪块儿区域存在地磁异常点。通过对5个台站采集的磁通门垂直分量数据进行挖掘,结果验证了算法用于分析航空磁测数据的有效性。
Difference form traditional point detection on the ground and near-earth electromagnetic detection onboard electromagnetic satellites,aeromagnetic field observation can collect larger region dataset for mining anomalies associated with earthquakes.The differential biclustering mining algorithm is used to mine aeromagnetic field datasets in different period with the same region.Through mining history magnetic datasets of five earthquake stations,the results demonstrate that the differential biclustering algorithm has significance for aeromagnetic field dataset analysis.
Difference form traditional point detection on the ground and near-earth electromagnetic detection onboard electromagnetic satellites,aeromagnetic field observation can collect larger region dataset for mining anomalies associated with earthquakes.The differential biclustering mining algorithm is used to mine aeromagnetic field datasets in different period with the same region.Through mining history magnetic datasets of five earthquake stations,the results demonstrate that the differential biclustering algorithm has significance for aeromagnetic field dataset analysis.
引文
[1]王淼,龚诚.数据挖掘技术在航空地磁场观测中的应用[C]//全国建成小康社会与中国航空发展——2013年首届中国航空科学技术大会论文集.2013.
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[4]Odibat O.Reddy C K.Giroux C N.Differential biclustering for gene expression analysis[C]//Proceedings of the First ACM International Conference on Bioinformatics and Computational Biology.2010:275-284.
[2]Wang M,Shang X Q,Li X Y,et al.Efficient mining differential co-expression biclusters in microarray datasets[J].Gene,2013,518(1):59-69.
[3]Pandey G,Atluri G,Steinbach M,et al.An association analysis approach to biclusting[C]//Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining.2009:677-686.
[4]Odibat O.Reddy C K.Giroux C N.Differential biclustering for gene expression analysis[C]//Proceedings of the First ACM International Conference on Bioinformatics and Computational Biology.2010:275-284.