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基于机器学习的预测和实验验证,重金属吸附能力的本托尼特

Lisheng Guo¹, Xin Xu¹, Cencen Niu¹

¹College of Construction Engineering, Jilin University, Changchun 130026, China.

The Science of the total environment

|March 29, 2024

概括

托尼特 (Bentonite) 是一种托尼特.

科学领域:

环境科学环境科学
材料科学材料科学材料科学
数据科学数据科学数据科学

背景情况:

石是一种天然吸附剂,广泛用于重金属的去除.
班托尼特的重金属吸附能力因其不同性质而有所不同.
需要准确的预测模型来优化土的应用.

研究的目的:

通过机器学习预测本托尼特的重金属吸附能力.
为了确定影响吸附的关键因素.
开发一个用户友好的预测工具.

主要方法:

评估了六个机器学习 (ML) 回归算法.
一个极端梯度增强回归 (XGB) 模型被开发和优化.
进行了特征重要性分析,以了解影响因素.

主要成果:

XGB模型显示出卓越的预测性能.
吸附条件是最有影响力的因素,其次是托尼特和重金属属性.
成功开发了一个基于Web的图形用户界面 (GUI).

结论:

XGB模型准确地预测了本托尼特的重金属吸附能力.
了解特征的重要性指导优化土石的修复.
开发的GUI工具增强了重金属污染控制的实际应用和效率.

关键词:

吸附能力吸附能力吸附能力托尼特 (Bentonite) 是一种托尼特.这是一种重金属,重金属.机器学习是机器学习.在XGBoost中使用.

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