物理化学学报 >> 1996, Vol. 12 >> Issue (05): 400-405.doi: 10.3866/PKU.WHXB19960504

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CmI奇宇称光谱能级的模式识别研究

曹晓卫,刘洪霖,陈念贻   

  1. 中国科学院上海冶金研究所，上海 200050
  • 收稿日期:1995-09-18 修回日期:1995-11-27 发布日期:1996-05-15
  • 通讯作者:

Study on the Curium I Odd-Parity Energy Levels Using Pattern Recognition Techniques

Cao Xiao-Wei,Liu Hong-Lin,Chen Nian-Yi   

  1. Shanghai Institute of Metallurgy,Chinese Academy of Sciences,Shanghai 200050
  • Received:1995-09-18 Revised:1995-11-27 Published:1996-05-15
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摘要：

应用新的模式识别方法PCA－BPN（Principal Component Analysis－Back Propagation Network）指认CmⅠ奇宇称未知能级，支持了前人应用传统的KNN（K Nearest Neighbors）等模式识别方法及对传神经网络方法（Counter Propagation Network，CPN）对大部分谱线的指认，进一步确认了这些组态的归属；鉴别了KNN等与CPN不同的预报结果，纠正CPN的某些错误分类，并以可视非线性映照分类器加以佐证

关键词: CmI奇宇称光谱, 能级分类, 模式识别, PCA-BP神经网络, 非线性映照

Abstract:

A new pattern recognition technique PCA-BPN(principal component analysis-back propagation network) has been used to assign the unknown electronic configurations of odd-parity energy levels of the first spectrum of curium (Cm I ). The obtained results show that (1) most previous predictions given by KNN(K nearest neighbours) and CPN(counter propagation network) are further confirmed;(2) several energy levels, which could not be clearly assigned by KNN etc., are predicted to be in good agreement with the assignments of the CPN;(3) two energy levels which were wrongly predicted by the CPN are now corrected using the PCA-BPN and the new assignments are supported by the traditional pattern recognition technique, PCA-NLM(principal component analysis nonlinear mapping).

Key words: Cm I odd parity spectrum, Classification of energy levels, Pattern recognition, PCA-BP neural network, Nonlinear mapping