Cheng Biao, Wu Xiao-hua, Chen De-zhao
Department of Chemical and Biological Engineering, Zhejiang University, Hangzhou 310027, China.
Guang Pu Xue Yu Guang Pu Fen Xi. 2006 Oct;26(10):1923-7.
Wavelength selection in PLS calibration can be used to reach two goals: improve the predictive ability and simplify the model. Iteratively reinitialized GA is a modified genetic algorithm, and it gives an initializing procedure of selecting the first candidates for every run of GA, which uses the results of previous runs as the guiding information. This algorithm can select wavelength regions instead of scattering points, which is very helpful in understanding the relevant parts of spectra. Furthermore, the continuous wavelength points make the PLS model more robust. Appling IRGA based wavelength selection to the UV-Vis spectrum of cough syrup, the result illustrates that PLS regression can greatly benefit from variable selection when used for multicomponent spectrophotometric determination.
偏最小二乘法（PLS）校准中的波长选择可用于实现两个目标：提高预测能力并简化模型。迭代重新初始化遗传算法（IRGA）是一种改进的遗传算法，它给出了在每次遗传算法运行时选择首批候选者的初始化过程，该过程将先前运行的结果用作指导信息。此算法可以选择波长区域而非散射点，这对于理解光谱的相关部分非常有帮助。此外，连续的波长点使PLS模型更加稳健。将基于IRGA的波长选择应用于止咳糖浆的紫外可见光谱，结果表明，在用于多组分分光光度测定时，PLS回归可以从变量选择中大大受益。
