网格聚类分析天文光谱数据

Analysis of Astronomical Spectral Data Based on Grid Clustering

应用互联网+融合信息技术,天文大数据研究实现了海量观测数据及次生数据的高效存储、检索、数据分析及信息挖掘。现结合我国自主知识产权的大科学工程LAMOST望远镜巡天第四期(DR4)发布的经定标后的光谱数据,运用R语言中RFITSIO软件包读写光谱专用文件FITS格式,读取LAMOST发布的恒星天文数据,结合统计学和数据挖掘方法设计了有监督的网格聚类验证方案,处理并识别光谱数据,经降维提取光谱特征,归一化连续谱,保留吸收谱线特征,再划分网格聚类波长定标中心,利用相似度量函数来描述识别观测光谱数据。

The efficient analysis and processing of astronomical data is supported by Internet plus integration information technology.The massive observation data and secondary data have achieved efficient storage,retrieval,data analysis and information mining.Combined with the fourth (DR4) released star spectral flowed calibration data of the large scientific engineering LAMOST telescope survey which has owned China's independent intellectual property rights,taking the astronomical data released by LAMOST as an example,RFITSIO software package of R language programming platform is used to read and write the spectrum documents of special FITS format.With the statistical data and data mining method,the verification scheme of supervised grid clustering was designed,by processing and identifying the spectral data.The spectral characteristics were extracted by dimensionality reduction.The characteristics of the absorption spectra were retained by normalized continuous spectrum,then the center grid of clustering wave length scale was divided,and the similarity measure function was used to describe the observed spectrum.