Soil Contamination 2011
DOI: 10.5772/23661
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Reflectance Spectroscopy as a Tool for Monitoring Contaminated Soils

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Cited by 42 publications
(59 citation statements)
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“…The independent data matrix (spectral data) is transformed by PCA, and the first few principal components (PCs), which show most of the independent data variance, are used as inputs for the MLR model instead of the original spectral data. 59 Schwartz et al 59 stated that the advantages of this method over SMLR are that the PCs are uncorrelated and the noise is filtered. The first few PCs are usually enough for a robust model, and over-fitting issues can be removed.…”
Section: 61mentioning
confidence: 99%
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“…The independent data matrix (spectral data) is transformed by PCA, and the first few principal components (PCs), which show most of the independent data variance, are used as inputs for the MLR model instead of the original spectral data. 59 Schwartz et al 59 stated that the advantages of this method over SMLR are that the PCs are uncorrelated and the noise is filtered. The first few PCs are usually enough for a robust model, and over-fitting issues can be removed.…”
Section: 61mentioning
confidence: 99%
“…Learn-ing is a repeating process in which the resulting output is compared to the given expected output and the algorithm adjusts the weights accordingly. 59 In a recent large-scale study that included over 1100 soil samples, ANN was proven to provide better results than PLSR in modeling soil constituents. 29 Although this method is often used to deal with nonlinear models, it is not popular with researchers due to some problems, such as the selection of hidden layer size, learning rate, and momentum.…”
Section: 61mentioning
confidence: 99%
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