研究正交信号校正(orthogonal signal correction,OSC)-小波包变换(wavelet packet transform,WPT)-偏最小二乘法(partial least squares,PLS)法用于不经化学分离直接解析荧光光谱严重重叠的色氨酸﹑酪氨酸和苯丙氨酸混合体系。本实验PO...研究正交信号校正(orthogonal signal correction,OSC)-小波包变换(wavelet packet transform,WPT)-偏最小二乘法(partial least squares,PLS)法用于不经化学分离直接解析荧光光谱严重重叠的色氨酸﹑酪氨酸和苯丙氨酸混合体系。本实验POSCWPTPLS程序执行相关计算,并将3种化学计量学方法(OSC-WPT-PLS、WPT-PLS和PLS)进行比较。3种氨基酸的总体相对预测标准偏差分别为2.80%、4.35%和5.14%,结果表明:OSC-WPT-PLS法优于WPT-PLS法和PLS法,将该法用于测定自来水及内蒙产的金骆驼酒和河套老窖酒中的色氨酸﹑酪氨酸和苯丙氨酸的含量及其回收率分别为96.9%～103.2%、94.1%～105.4%、95.3%～107.8%,取得良好效果。展开更多
Information analysis of high dimensional data was carried out through similarity measure application. High dimensional data were considered as the a typical structure. Additionally, overlapped and non-overlapped data ...Information analysis of high dimensional data was carried out through similarity measure application. High dimensional data were considered as the a typical structure. Additionally, overlapped and non-overlapped data were introduced, and similarity measure analysis was also illustrated and compared with conventional similarity measure. As a result, overlapped data comparison was possible to present similarity with conventional similarity measure. Non-overlapped data similarity analysis provided the clue to solve the similarity of high dimensional data. Considering high dimensional data analysis was designed with consideration of neighborhoods information. Conservative and strict solutions were proposed. Proposed similarity measure was applied to express financial fraud among multi dimensional datasets. In illustrative example, financial fraud similarity with respect to age, gender, qualification and job was presented. And with the proposed similarity measure, high dimensional personal data were calculated to evaluate how similar to the financial fraud. Calculation results show that the actual fraud has rather high similarity measure compared to the average, from minimal 0.0609 to maximal 0.1667.展开更多
文摘研究正交信号校正(orthogonal signal correction,OSC)-小波包变换(wavelet packet transform,WPT)-偏最小二乘法(partial least squares,PLS)法用于不经化学分离直接解析荧光光谱严重重叠的色氨酸﹑酪氨酸和苯丙氨酸混合体系。本实验POSCWPTPLS程序执行相关计算,并将3种化学计量学方法(OSC-WPT-PLS、WPT-PLS和PLS)进行比较。3种氨基酸的总体相对预测标准偏差分别为2.80%、4.35%和5.14%,结果表明:OSC-WPT-PLS法优于WPT-PLS法和PLS法,将该法用于测定自来水及内蒙产的金骆驼酒和河套老窖酒中的色氨酸﹑酪氨酸和苯丙氨酸的含量及其回收率分别为96.9%～103.2%、94.1%～105.4%、95.3%～107.8%,取得良好效果。
基金Project(RDF 11-02-03)supported by the Research Development Fund of XJTLU,China
文摘Information analysis of high dimensional data was carried out through similarity measure application. High dimensional data were considered as the a typical structure. Additionally, overlapped and non-overlapped data were introduced, and similarity measure analysis was also illustrated and compared with conventional similarity measure. As a result, overlapped data comparison was possible to present similarity with conventional similarity measure. Non-overlapped data similarity analysis provided the clue to solve the similarity of high dimensional data. Considering high dimensional data analysis was designed with consideration of neighborhoods information. Conservative and strict solutions were proposed. Proposed similarity measure was applied to express financial fraud among multi dimensional datasets. In illustrative example, financial fraud similarity with respect to age, gender, qualification and job was presented. And with the proposed similarity measure, high dimensional personal data were calculated to evaluate how similar to the financial fraud. Calculation results show that the actual fraud has rather high similarity measure compared to the average, from minimal 0.0609 to maximal 0.1667.
