基于机器学习的水质多变量分析估计
机器学习
2025-12-03 v1
摘要
水质是农业食品领域水质的关键因素。农业中用于灌溉、畜牧业以及农业食品加工工业都需要使用水。随着该领域数字化进程的推进，水质的自动评估因此成为重要的资产。在本工作中，我们展示了将紫外-可见（UV-Vis）光谱与机器学习集成于水质评估背景中的应用，旨在确保水安全和水质法规合规。Furthermore, we emphasize the importance of model interpretability by employing SHapley Additive exPlanations (SHAP) to understand the contribution of absorbance at different wavelengths to the predictions. Our approach demonstrates the potential for rapid, accurate, and interpretable assessment of key water quality parameters.
引用
@article{arxiv.2512.02508,
title = {Water Quality Estimation Through Machine Learning Multivariate Analysis},
author = {Marco Cardia and Stefano Chessa and Alessio Micheli and Antonella Giuliana Luminare and Francesca Gambineri},
journal= {arXiv preprint arXiv:2512.02508},
year = {2025}
}
备注
The paper has been accepted at Italian Workshop on Neural Networks (WIRN) 2024