Regularization of Parallel Factor Analysis (PARAFAC): A New Approach to Determining Groups of Fluorophores in Fluorescence Spectra of Natural Waters

IF 0.8 4区 化学 Q4 SPECTROSCOPY Journal of Applied Spectroscopy Pub Date : 2024-11-19 DOI:10.1007/s10812-024-01821-w
I. N. Krylov, O. N. Erina, A. N. Drozdova, I. V. Seliverstova, T. A. Labutin
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Abstract

Parallel factor analysis (PARAFAC) is widely used in relation to fluorescence excitation/emission spectra to track the movement of water masses and to study seasonal changes in the composition and content of dissolved organic matter. The stage of selecting the number of components is one of the most difficult when using factor analysis. The widely used method of analyzing loads when splitting the original set into halves in many cases does not allow a determination of the best model because of the closeness of their statistical estimates. Because the use of regularization with a penalty for the sum of parameter modules tends to lead to sparse solutions in which some of the coefficients are equal to zero, the use of this approach allows one to select those variables that carry useful information. A procedure is proposed for selecting the number of components when performing parallel factor analysis of fluorescence spectra using a penalty for the 1- and 2-norms of the solution.

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并行因子分析正则化(PARAFAC):确定天然水荧光光谱中荧光团的新方法
平行因子分析(PARAFAC)被广泛应用于荧光激发/发射光谱,以追踪水团的运动,研究溶解有机物的组成和含量的季节性变化。在使用因子分析时,选择成分数量是最困难的阶段之一。将原始数据集分成两半时,广泛使用的载荷分析方法在很多情况下无法确定最佳模型,因为它们的统计估计值非常接近。由于使用对参数模块总和进行惩罚的正则化方法往往会导致部分系数等于零的稀疏解,因此使用这种方法可以选择那些携带有用信息的变量。本文提出了一种程序,用于在对荧光光谱进行并行因子分析时选择分量的数量,该程序使用了对解的 1 次方和 2 次方的惩罚。
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来源期刊
CiteScore
1.30
自引率
14.30%
发文量
145
审稿时长
2.5 months
期刊介绍: Journal of Applied Spectroscopy reports on many key applications of spectroscopy in chemistry, physics, metallurgy, and biology. An increasing number of papers focus on the theory of lasers, as well as the tremendous potential for the practical applications of lasers in numerous fields and industries.
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