CmⅠ奇宇称光谱能级的模式识别研究

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

应用新的模式识别方法PCA－BPN（PrincipalComponentAnalysis－BackPropagationNetwork）指认CmⅠ奇宇称未知能级，支持了前人应用传统的KNN（KNearestNeighbors）等模式识别方法及对传神经网络方法（CounterPropagationNetwork，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。

A new pattern recognition technique PCA-BPN(principal component analysisback propagation network) has been used to assign the unknown electronic configurations of odd-parity energy levels of the first spectrum of curiurn (Cm I ). The obtained results show that (1) most previous predictions given by KNN(K nearest neighbours) and CPN(counter propagation network) are further codemed;(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 assignxnents are supported by the traditional pattern recognition tedrique, PCA-NLM(principal component analysisnonlinear mapping).