High and low frequency unfolded partial least squares regression based on empirical mode decomposition for quantitative analysis of fuel oil samples

Analytica Chimica Acta

Volumn 925, Issue , 2016, Pages 16-22

  Bian, Xihui ^a   Li, Shujuan ^a   Lin, Ligang ^a   Tan, Xiaoyao ^a   Fan, Qingjie ^b   Li, Ming ^a  

^a TIANJIN POLYTECHNIC UNIVERSITY   (China)

^b Green (Tianjin) Technology Development Company Ltd   (China)

Author keywords

Complex sample analysis; Empirical mode decomposition; Ensemble modeling; Partial least squares regression; Unfolded strategy

Indexed keywords

FUEL OILS; HYDROCARBON REFINING; HYDROCARBONS; LEAST SQUARES APPROXIMATIONS; PREDICTIVE ANALYTICS; REGRESSION ANALYSIS; SIGNAL PROCESSING; URANIUM METALLOGRAPHY; VANADIUM METALLOGRAPHY;

COMPLEX SAMPLES; EMPIRICAL MODE DECOMPOSITION; ENSEMBLE MODELING; PARTIAL LEAST SQUARES REGRESSION; UNFOLDED STRATEGY;

TIME DOMAIN ANALYSIS;

FUEL OIL; HYDROCARBON;

ACCURACY; ALGORITHM; ARTICLE; CONTROLLED STUDY; DECOMPOSITION; HUMAN; PARTIAL LEAST SQUARES REGRESSION; PRIORITY JOURNAL; QUANTITATIVE ANALYSIS; SIGNAL PROCESSING; ULTRAVIOLET SPECTROSCOPY;

EID: 84992311939     PISSN: 00032670     EISSN: 18734324     Source Type: Journal    
DOI: 10.1016/j.aca.2016.04.029     Document Type: Article

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