Spectral classification and particular spectra identification based on data mining
Spectral classification and particular spectra identification based on data mining
复制标题
基于数据挖掘的光谱分类和特定光谱识别
DOI：
10.1007/s11831-020-09401-9
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发表时间：
2021
影响因子：
9.7
通讯作者：
Mengxin Wang
中科院分区：
文献类型：
--
作者：
Peng Yang;Guowei Yang;Fanlong Zhang;Bing Jiang;Mengxin Wang
光谱分类和特征光谱识别是天体天文学研究的主要任务。随着大规模光谱测量的发展，大量的光谱数据可以很容易地获得，各种数据挖掘方法被广泛应用于天文学家的自动光谱分析。本文对这些方法进行了详细的综述，并分析了它们的优缺点。此外，有代表性的方法的实验结果报告和讨论从不同的角度，包括训练和测试样本的数量，特征提取方案，分类器的选择和性能评价。最后指出了存在的问题和未来的研究方向。
Spectral classification and particular spectra identification are primary tasks for celestial object study in astronomy. With the developing of large spectrographic surveys, huge volumes of spectral data can be easily obtained and various data mining methods have been widely applied to assist astronomers for automatic spectral analysis. In this paper, we review these methods in detail and analyze their advantages as well as disadvantages. Moreover, experimental results of the representative methods are reported and discussed from different perspectives, including number of training and testing samples, feature extraction scheme, classifier selection and performance evaluation. Finally, we point out the existing problems and the potential research trend.