【摘要】 利用模式识别的主成分分析法 (PCA- Principal Component Analysis)对 Cm 奇宇称光谱的电子组态进行分类 ,得出 5 f87p、 5 f76 d7s、 5 f76 d2各组态间的分类判据。结果表明 :选择适当的模式识别方法和空间投影 ,寻找组态间的分类判据 ,可以有效地对原子光谱的电子组态进行分类和预报 ,是原子光谱分析的一种有用的方法。更多还原

【Abstract】 The principal component analysis, one of pattern recognition methods, is applied to classification of electronic configuration of the odd parity spectrum of curium (CmⅡ) and some criteria for classification of configurations among 5f 87p、5f 76d7s、5f 76d 2 are obtained. The results show that electronic configurations of atomic spectrum can be assigned and predicted effectively by classification criteria obtained by both pattern recognition and space mapping, which are useful for atomic spectrum analysis.更多还原