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区间偏最小二乘结合差分进化算法应用于鱼粉近红外光谱波长筛选
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作者单位
张优优,陈伟豪,唐志敏,辜洁,莫丽娜,陈华舟 1.桂林理工大学理学院2.重庆人文科技学院机电与信息工程学院3.桂林理工大学大数据处理与算法技术研究中心 
基金项目:国家自然科学基金(61505037);广西自然科学基金(2018GXNSFAA050045)
中文摘要:蛋白质含量是评价鱼粉质量的重要指标,该文采用近红外(NIR)光谱分析技术结合特征筛选方法建立了鱼粉蛋白质含量的快速定量分析模型,并结合区间偏最小二乘(iPLS)和二进制变异策略的差分进化(DE)算法建立了区间偏最小二乘差分进化(iPLS-DE)的波长筛选优化模式,对鱼粉NIR光谱数据进行特征波长筛选。iPLS-DE通过调试iPLS中等分子区间的数量,优选出9个最优特征波段,再采用二进制变异策略的DE算法在最优特征波段内筛选离散特征波长组合,最后根据模型的评价指标确定iPLS-DE优选模型并与iPLS优选模型进行比较。结果表明,将鱼粉全谱等分为5个子区间时,iPLS-DE筛选出50个离散特征波长建立的优选模型对测试集样品的预测均方根误差和相对分析误差分别为1.033%和4.058,而iPLS优选模型对测试集样品的预测均方根误差和相对分析误差分别为1.131%和3.855。表明iPLS-DE方法能够有效地提高NIR光谱分析模型对鱼粉蛋白质定量检测的预测能力。
中文关键词:近红外光谱  鱼粉蛋白质  特征提取  区间偏最小二乘  差分进化算法
 
Application of Interval Partial Least Squares with Differential Evolution Algorithm in Wavelength Selection of Near Infrared Spectroscopy for Fishmeal
Abstract:Protein content is an important indicator for the evaluation of the quality of fishmeal.In this paper,a near infrared(NIR) spectral analysis technique combined with a feature selection method was adopted to establish a rapid quantitative analytical model detecting the protein content of fishmeal samples.Combining the interval partial least squares(iPLS) with the differential evolution(DE) algorithms of binary mutation strategy,a novel optimization mode,ie.interval partial least squares differential evolution(iPLS-DE) was established for the wavelength selection of the NIR spectral data for fishmeal samples.9 optimal feature wavebands were first selected by iPLS-DE through adjusting the number of equally divided intervals in iPLS,and then the discrete characteristic wavelength combinations in the optimal wavebands were further to screened out by the DE algorithm of binary mutation strategy.According to the evaluation indexes for the model,the optimal model of iPLS-DE was determined,and compared with the optimal model of iPLS.Results showed that,when the full spectrum was equally divided into 5 intervals,50 discrete characteristic wavelengths were screened out by iPLS-DE to establish an optimal model.The prediction root mean square error and relative prediction derivation of the iPLS-DE optimization model for the test set samples were 1.033% and 4.058,while the prediction root mean square error and relative prediction derivation of the iPLS optimization model for the test set samples were 1.131% and 3.855,respectively.In comparison with the common iPLS models,the iPLS-DE model is more feasible to improve the predictive ability of NIR analytical model applied to the quantitative detection of fishmeal protein.
Key Words:near infrared spectroscopy  fishmeal protein  feature extraction  interval partial least squares  differential evolution
引用本文:张优优,陈伟豪,唐志敏,辜洁,莫丽娜,陈华舟.区间偏最小二乘结合差分进化算法应用于鱼粉近红外光谱波长筛选[J].分析测试学报,2020,39(11):1392-1397.
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