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Aplica??o de técnicas multivariadas e inteligência artificial na análise de espectros de infravermelho para determina??o de matéria organica em amostras de solos

机译:多元技术和人工智能在红外光谱分析中测定土壤样品中有机物的应用

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In this paper studies based on Multilayer Perception Artificial Neural Network and Least Square Support Vector Machine (LS-SVM) techniques are applied to determine of the concentration of Soil Organic Matter (SOM). Performances of the techniques are compared. SOM concentrations and spectral data from Mid-Infrared are used as input parameters for both techniques. Multivariate regressions were performed for a set of 1117 spectra of soil samples, with concentrations ranging from 2 to 400 g kg-1. The LS-SVM resulted in a Root Mean Square Error of Prediction of 3.26 g kg-1 that is comparable to the deviation of the Walkley-Black method (2.80 g kg-1).
机译:本文基于多层感知人工神经网络和最小二乘支持向量机(LS-SVM)技术进行研究,确定土壤有机质(SOM)的浓度。比较了这些技术的性能。来自中红外的SOM浓度和光谱数据用作这两种技术的输入参数。对一组1117个土壤样品光谱进行了多元回归分析,浓度范围为2至400 g kg-1。 LS-SVM得出的预测均方根误差为3.26 g kg-1,与Walkley-Black方法的偏差(2.80 g kg-1)相当。

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