Influence of wavelet transform settings on NIR and MIR spectrometric analyses of diesel, gasoline, corn and wheat

Journal of the Brazilian Chemical Society

Galvão, Roberto K. H.¹  Pinto, Luiz Alberto¹  Araújo, Mário César U.¹  Instituto Tecnológico de Aeronáutica, São José dos Campos, Brazil¹  Universidade Federal da Paraíba, João Pessoa, Brazil¹ 

关键词: multivariate calibration;    wavelet transform;    analysis of variance;    mid and near infrared spectrometry;    food and fuel analysis;   

DOI  :  10.1590/S0103-50532011000100025

学科分类：化学（综合）

来源: SciELO

【 摘 要 】

This paper investigates the influence of wavelet family, length and number of resolution levels on the performance of multivariate calibration models obtained in the wavelet domain. Twenty-one physical and chemical properties of diesel, gasoline, corn and wheat were determined by near/mid infrared spectrometry employing partial least-squares (PLS) and stepwise regression (SR) in the original and wavelet domains. Through proper selection of the wavelet transform settings, average RMSEP reductions of 8.2% (PLS) and 27.0% (SR) were obtained with respect to the original domain. However, the SR models presented considerable sensitivity with respect to the choice of transform settings. In this case, an analysis of variance indicated that the number of resolution levels is the most important factor to be considered.

【 授权许可】

Unknown