基于区间组合移动窗口法筛选近红外光谱信息

摘要

Selection of near infrared spectral information is research focus on the application of NIR, which enable to simplify the model and improve accuracy of prediction.Aiming at selecting optimal modeling spectral width of near infrared spectroscopy, section combination moving window partial least squares (SCMWPLS) is proposed in this paper.This method selects continuous modeling screened interval.by continuously varying size of moving window and cross validation.Taking Glucose solution near-infrared spectroscopy as test specimen, near infrared prediction models are established respectively by proposed method, and traditional interval partial least squares (IPLS) and moving window partial least squares (MWPLS).Comparing proposed method with two traditional methods, squares prediction RMSE is decreased by 44% and 25% respectively.%近红外光谱信息的筛选方法是近红外光谱技术简化模型和提高预测精度的重要手段,为选择近红外光谱分析中最优的建模光谱波段,提出区间组合移动窗口偏最小二乘法(SCMWPLS).该方法通过大小连续变化的移动窗口和交叉有效性筛选出连续的建模区间.以葡萄糖溶液的近红外光谱为测试对象,分别采用所提方法以及传统的间隔偏最小二乘法(IPLS)和窗口移动偏最小二乘法(MWPLS)建立近红外光谱预测模型.所提方法与传统的间隔偏最小二乘法和窗口移动偏最小二乘法模型相比,预测均方根误差分别降低了44%和25%.