Ding Q, Small G W, Arnold M A
Department of Chemistry & Biochemistry, Ohio University, Athens 45701, USA.
Anal Chem. 1998 Nov 1;70(21):4472-9. doi: 10.1021/ac980451q.
An improved genetic algorithm (GA)-based wavelength selection procedure is developed to optimize both the near-infrared wavelengths used and the number of latent variables employed in building partial least-squares (PLS) calibration models. This GA-based wavelength selection algorithm is applied to the determination of glucose in two different biological matrixes. With random selection of a small number of initial wavelengths, a dramatic reduction in the number of wavelengths required for building the PLS calibration models is observed. The fitness function used to guide the GA, the method of recombination used, and the effect of spectral resolution on the wavelength selection are also studied. In the resolution study, the original data with a point spacing of 2 cm-1 are deresolved to 4-, 8-, and 16-cm-1 point spacings by truncating the collected interferograms before applying the Fourier processing step. The use of lower resolution spectra is found to reduce further the number of final wavelengths selected by the GA, and the performance of the optimal calibration models obtained with the original spectra is maintained with the lower resolution spectra of both 4- and 8-cm-1 point spacing. Degradation in performance is observed with the spectra computed with a point spacing of 16 cm-1, however.
开发了一种基于改进遗传算法（GA）的波长选择程序，以优化用于构建偏最小二乘（PLS）校准模型的近红外波长以及所采用的潜在变量数量。将这种基于GA的波长选择算法应用于两种不同生物基质中葡萄糖的测定。通过随机选择少量初始波长，观察到构建PLS校准模型所需的波长数量大幅减少。还研究了用于指导GA的适应度函数、所采用的重组方法以及光谱分辨率对波长选择的影响。在分辨率研究中，通过在应用傅里叶处理步骤之前截断收集的干涉图，将点间距为2 cm-1的原始数据降分辨率为4、8和16 cm-1的点间距。发现使用较低分辨率光谱可进一步减少GA选择的最终波长数量，并且对于4 cm-1和8 cm-1点间距的较低分辨率光谱，获得的最佳校准模型的性能与原始光谱保持一致。然而，对于点间距为16 cm-1计算得到的光谱，观察到性能下降。
