光学精密工程2025，Vol.33Issue(20)：3192-3202,11.DOI:10.37188/OPE.20253320.3192
改进黑翅鸢算法优化的XGBoost可解释模型在转基因棉籽油太赫兹光谱鉴别中的应用
Application of XGBoost explainable model improved by black-winged kite algorithm optimization in the identification of genetically modified cotton seed oil by terahertz spectroscopy
摘要
Abstract
To achieve accurate classification and identification of genetically modified and non-genetically modified cottonseed oil,this study proposes an explainable classification model based on an improved black-winged kite algorithm optimized extreme gradient boosting(XGBoost)model.First,a terahertz time-domain spectroscopy(THz-TDS)system was used to collect terahertz absorption spectra of geneti-cally modified and non-genetically modified cottonseed oil samples in the 0.3-1.8 THz frequency range.Then,the traditional Black-winged Kite algorithm(BKA)was improved by introducing a dual-objective fitness function optimization strategy,a reverse learning initial population strategy,and a Rayleigh distribu-tion function to control the Lévy flight strategy.The improved Black-winged Kite algorithm(DLBKA)was used to perform dual-objective hyperparameter optimization of the tree depth,learning rate,and maxi-mum iteration count of the XGBoost model,thereby constructing the DLBKA-XGBoost classification model.Finally,the model was applied to identify genetically modified cottonseed oil,and the model's identification results were analyzed for interpretability using the SHAP method.The results showed that the improved Black-winged Kite Algorithm-optimized XGBoost interpretable classification model not only improved the accuracy of identifying genetically modified and non-genetically modified cottonseed oil(with a test set accuracy as high as 97.78%,an improvement of 4.45%over the traditional Black-winged Kite algorithm-optimized model,an improvement of 14.45%over the traditional Whale Optimization Algo-rithm(WOA)-optimized model),but also provided explanations for the model,clarifying the positive in-fluence mechanism of key feature frequencies on the identification results,thereby enhancing the model's transparency and credibility.Therefore,this study provides a fast and accurate analytical method for the identification of genetically modified cottonseed oil and offers valuable references for the identification of other genetically modified substances.关键词
太赫兹光谱/转基因棉籽油/极端梯度提升/改进黑翅鸢算法/可解释性分析Key words
Terahertz spectroscopy/genetically modified cottonseed oil/extreme gradient boosting/im-proved black-winged kite algorithm/explainability analysis分类
数理科学引用本文复制引用
陈涛,赵利..改进黑翅鸢算法优化的XGBoost可解释模型在转基因棉籽油太赫兹光谱鉴别中的应用[J].光学精密工程,2025,33(20):3192-3202,11.基金项目
国家自然科学基金资助项目(No.62261012,No.62261012) （No.62261012,No.62261012）
