In this paper, the performances of four improved analytical methods (backward stepwise selection of peak intensities, sum of characteristic peaks of a component, moving window partial least squares, and genetic algorithms) using wavelength selection for the analysis of xylene mixtures by Raman spectroscopy are tested for further use on the new “digital micromirror device associated with a photomultiplier tube” Raman spectrometer. It is shown that the errors of prediction using only a few selected points (from 4 to 49 depending on the method) are almost the same as when using the whole spectral range (1050 points). Compared to the last two methods, the “backward stepwise selection of peak intensities” and “sum of characteristic peaks of a component” methods are robust under industrial conditions and appear to be well suited for chemical quantitative analysis with the new Raman spectrometer, which allows the measurements of the total intensity to be made simultaneously for a number of pre-selected frequencies. Results show that the errors of prediction can be near to or even lower than 2%.
Work Function Algorithm with a Moving Window for Solving the On-Line k-Server Problem
