An adaptive wavelength interval selection by modified particle swarm optimization algorithm: simultaneous spectral or differential pulse voltammetric determination of multiple components with overlapping peaks

The elimination of wavelengths which contain useless or irrelevant information for calibration model is becoming one of the key steps in multicomponent spectral analysis even in situations where the partial least-squares (PLS) regression is applied. Because of the continuity of most kinds of spectral responses, the adaptive wavelength interval selection by modified particle swarm optimization (PSO) could be proposed in the present study. The proposed method was used for simultaneous spectrophotometric determination of caffeine, aspirin, and phenacetin and simultaneous differential pulse voltammetric determination of nitrophenol isomers. The method was eventually applied to commercial drugs. For comparison, a conventional full-spectrum PSO analysis was also performed. Experimental results demonstrate that the adaptive wavelength interval selection by modified PSO is capable of improving the future predictive ability of the model.