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Use Of Radial Basis Function Networks And Near-infrared Spectroscopy For The Determination Of Total Nitrogen Content In Soils From Sao Paulo State

机译:径向基函数网络和近红外光谱法测定圣保罗州土壤中的总氮含量

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摘要

Total nitrogen has been determined by using a model developed between the conventional chemical measurements and diffuse reflectance spectra in the near-infrared region. Samples (244) from different types of soils with total nitrogen contents ranging from 0.20 to 13.60% (m/m) were modeled by partial least-squares regression (PLS), multi-layer perceptron feed-forward networks (MLP) and radial basis function networks (RBFN). The RBFN model produced a better square error of prediction (SEP) of 0.048 and R2 = 0.93 in a procedure that is simpler, faster and less dependent on the initial conditions. 2008 © The Japan Society for Analytical Chemistry.
机译:总氮已通过使用在常规化学测量和近红外区域的漫反射光谱之间开发的模型确定。通过偏最小二乘回归(PLS),多层感知器前馈网络(MLP)和径向模型对来自不同类型土壤的总氮含量为0.20至13.60%(m / m)的样品(244)进行建模功能网络(RBFN)。 RBFN模型在更简单,更快且对初始条件的依赖性较小的过程中产生了更好的预测均方误差(SEP)为0.048,R2 = 0.93。 2008©日本分析化学学会。

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