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arXiv · 1507.05834

Improved quantification of naphthalene using non-linear Partial Least Squares Regression

Manuel Bastuck·Martin Leidinger·Tilman Sauerwald·Andreas Schütze
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Abstract

A test dataset is generated using temperature cycled operation with a WO3 metal oxide semiconductor (MOS) gas sensor. Six concentrations of naphthalene from 0 to 40 ppb are measured and, subsequently, used to evaluate the performance of three variants of Partial Least Squares Regression (PLSR). Ordinary PLSR produces highly non-linear models due to the non-linear response of the sensor. Double-logarithmic data results in a model with much better linearity which has a resolution of 4 ppb in the range from 0 to 20 ppb. The more complex Locally Weighted PLSR (LW-PLSR) produces an even better model, especially for higher concentrations, without making any assumptions for relationships in the underlying data.

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Manuel Bastuck, Martin Leidinger, Tilman Sauerwald, Andreas Schütze. 2015-07-21. Improved quantification of naphthalene using non-linear Partial Least Squares Regression. https://arxiv.org/abs/1507.05834

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