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基于几种新化学计量学方法,提出了可自动解析化学演进数据的新途径.在该法中,首先选择关键向量.通过子空间比较法确定数据的化学秩.以关键向量为起点,通过初等变换不断迭代而实现对数据的解析.并利用数据非负性等检验解析结果的可靠程度.结合GC-MS数据的特点,选择的关键变量可为关键质谱或关键浓度曲线.该方法能极大地减少人为干预,大大降低数据分析时间.对文中的石油样本共解析出557个成分.
Based on several new chemometrics methods, a new approach to automatically analyze chemical evolution data is proposed, in which the key vector is first selected, and the chemical rank of the data is determined by the subspace comparison method.From the key vector, Transform continuous iteration to achieve data analysis, and the use of non-negative data to test the reliability of analytical results.Combined with the characteristics of GC-MS data, the key variables can be selected as the key mass spectrometry or key concentration curve.The method can greatly Reduce human intervention, greatly reduce the data analysis time.A total of 557 constituents were extracted from the petroleum samples in this paper.