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Application of XGBoost explainable model improved by black-winged kite algorithm optimization in the identification of genetically modified cotton seed oil by terahertz spectroscopy
Modern Applied Optics | 更新时间：2025-12-02

    • Application of XGBoost explainable model improved by black-winged kite algorithm optimization in the identification of genetically modified cotton seed oil by terahertz spectroscopy

    • “In the field of food safety, researchers have proposed an interpretable classification model based on an improved black winged kite algorithm to optimize the XGBoost model, providing a fast and accurate analysis method for identifying genetically modified cottonseed oil.”
    • Optics and Precision Engineering   Vol. 33, Issue 20, Pages: 3192-3202(2025)

    • DOI：10.37188/OPE.20253320.3192    

      CLC： O439
    • CSTR：32169.14.OPE.20253320.3192    

    • Received：25 June 2025，

      Revised：2025-08-17，

      Published：25 October 2025

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  • CHEN Tao,ZHAO Li.Application of XGBoost explainable model improved by black-winged kite algorithm optimization in the identification of genetically modified cotton seed oil by terahertz spectroscopy[J].Optics and Precision Engineering,2025,33(20):3192-3202. DOI： 10.37188/OPE.20253320.3192. CSTR： 32169.14.OPE.20253320.3192.

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