A new strategy of applying modeling indicator determined method to high-level fusion for quantitative analysis.

Abstract

A novel method, named as modeling indicator determined (MID) method, based on two model evaluation parameters i.e., root mean square error of prediction (RMSEP) and ratio performance deviation (RPD), is proposed to employ high-level fusion for quantitative analysis. The two MID methods of root mean square error of prediction weighted (RMSEPW) method and ratio performance deviation weighted (RPDW) method are put forward on the basis of the model evaluation indicators from the individual models. Performance of RMSEPW method and RPDW method are evaluated in terms of the predictive ability of root mean square error of prediction for fusion (RMSEPf) through the fused models. The two MID methods are applied to UV-visible (UV-vis), near infrared (NIR) and mid-infrared (MIR) spectral data of active ingredient in pesticide, and gas chromatography-mass spectrometer (GC-MS) and NIR spectral data of n-heptane in chemical complex for high-level fusion. Moreover, the results are compared with the individual methods. As a result, the overall results show that the two MID methods are promising with significant improvement of predictive performance for high-level fusion when executing quantitative analysis.