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基于机器学习的复杂水文地质条件地区地下水中硫酸盐度的预测

Yushan Tian1, Quanli Liu1, Yao Ji1

  • 1State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China.

The Science of the total environment
|February 29, 2024
PubMed
概括

地下水中硫酸盐水平的上升带来了环境风险. 机器学习模型,特别是反向传播神经网络 (BPNN),有效预测硫酸盐度,确定矿井排水作为关键来源并帮助地下水保护战略.

关键词:
反向传播的神经网络.地下水的地下水.随机的森林随机的森林自组织地图的自我组织地图硫酸盐是一种硫酸盐.支持矢量机器的支持矢量机器.

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