相关实验视频

Updated: Jun 19, 2025

Watershed Planning within a Quantitative Scenario Analysis Framework

Watershed Planning within a Quantitative Scenario Analysis Framework

Published on: July 24, 2016

推进地下水质量预测:机器学习挑战和解决方案

Juan Antonio Torres-Martínez¹, Jürgen Mahlknecht¹, Manish Kumar²

¹Escuela de Ingeniería y Ciencias, Tecnologico de Monterrey, Campus Monterrey, Eugenio Garza Sada 2501, Monterrey, NL 64849, Mexico.

The Science of the total environment

|July 25, 2024

概括

机器学习 (ML) 显著推进了地下水质量研究. 然而,许多研究忽视了关键数据预处理 (83%) 和模型解释性 (15%),阻碍了准确的污染预测和可持续管理.

科学领域:

环境科学环境科学
数据科学数据科学数据科学
水文地质学水文地质学

背景情况:

机器学习 (ML) 对于预测和管理地下水污染变得越来越重要.
一份对230篇论文的综合审查强调了ML在环境科学中的演变和应用.
了解目前在地下水质量研究中的ML应用对于未来的进步至关重要.

研究的目的:

批判性地审查ML在地下水质量研究中的进步和挑战.
识别当前ML方法的缺陷,包括预处理和可解释性.
为建立地下水研究ML的最低标准提供框架.

主要方法:

对230篇关于ML和地下水质量的研究论文进行了系统的文献审查.
对ML实现的分析,重点是预处理,优化和可解释性.
对ML算法和性能指标的报告标准的评估.

主要成果:

大多数研究 (83%) 忽略了重要的数据预处理步骤,影响了模型的准确性.
虽然模型优化很常见 (65%),但模型的解释性仍然很低 (15%).
对算法的比较评估和适当的指标选择往往不足以评估模型可靠性.

结论:

在ML地下水研究中,有必要提高方法论的严谨性,特别是在数据预处理和模型解释性方面.
需要跨学科的合作和持续的创新,才能充分利用ML来实现可持续的地下水管理.
这一审查提供了一个框架,以指导在地下水质量评估中开发强大的ML应用程序.

关键词:

地下水质量地下水质量机器学习机器学习预测建模的预测建模.监督学习学习监督学习水污染指标水污染指标

更多相关视频

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma

Published on: October 10, 2018

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

Published on: December 9, 2012

相关概念视频

Gradually Varying Flow

Gradually Varying Flow

Gradually varying flow (GVF) in open channels describes situations where water depth changes slowly along the channel due to factors like non-uniform bed slope, channel shape variations, or obstructions. This flow type occurs when the depth adjusts gradually to balance gravitational forces, shear forces, and energy requirements, resulting in a low rate of depth change.Characteristics of Gradually Varying FlowGVF is commonly observed in natural streams, rivers, and canals, where flow depth...

Levels of Use of a GIS

Levels of Use of a GIS

Geographic Information Systems (GIS) operate across three levels of application, each representing an increasing degree of complexity: data management, analysis, and prediction. These levels reflect the expanding functionality and versatility of GIS technology in handling spatial data for diverse purposes.Data ManagementAt its foundational level, GIS serves as a tool for data management, enabling the input, storage, retrieval, and organization of spatial data. This level is often employed in...

Typical Model Studies

Typical Model Studies

Fluid mechanics model studies often utilize scaled-down systems to predict fluid behavior in full-scale environments, such as river flows, dam spillways, and structures interacting with open surfaces. Maintaining Froude number similarity in river models is crucial, as it replicates surface flow features like wave patterns and velocities.