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Updated: Jan 30, 2026

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根据可解释的机器学习模型预测流域中重金属的生态风险:在数据稀缺的框架下

Hong Chen1,2, Meiling Kong2, Zhenghua Wu2

  • 1School of Environment and Energy Engineering, Anhui Jianzhu University, Hefei, 230601, China.

Environmental monitoring and assessment
|January 28, 2026
PubMed
概括

使用SMOGN的合成数据生成显著改善了机器学习模型的准确性,用于预测流域生态系统中的重金属毒性. 这种方法加强了生态风险评估,并支持了污染控制战略.

关键词:
生态风险评估评估生态风险评估重金属是一种重金属.机器学习模型的机器学习模型莎普利的添加式解释合成少数群体过量采样技术用于高斯噪声回归.

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