遗传算法用于偏最小二乘方法建模中的变量筛选

利用全局搜索方法－遗传算法（genetic algorithms,GA)对近红外光谱分析中的波长变量进行筛选，再用偏最小二乘方法（patrial least squares,PLS）建立分析校正模型。对两类样品的近红外光谱分析应用实例表明，这种选取变量进行校正的方法，不仅简化、优化了模型，而且增强了所建模型的预测能力，尤其适用于单纯PLS较以校正关联的体系。

Variable Selection for Partial Least Squares Modelingby Genetic Algorithms

Genetic algorithms (GA), a global searching method, is applied to select wavelength variables of near infrared spectroscpy (NIR) for multivariate calibration made by partial least squares (PLS) method. Two application examples of NIR analysis show that this wavelength selection method for PLS modeling not only simplifies and optimizes calibration model but also increases the prediction ability of calibration model. The method is especially adequate for the system where only PLS is difficult to correlate.