Spatial distribution and source identification of potentially toxic elements in Yellow River Delta soils, China: An interpretable machine-learning approach-Reference-Cited by-同舟云学术

Spatial distribution and source identification of potentially toxic elements in Yellow River Delta soils, China: An interpretable machine-learning approach

Published:2024-02 Issue: Volume:912 Page:169092
ISSN:0048-9697
Container-title:Science of The Total Environment
language:en
Short-container-title:Science of The Total Environment

Author:

Zhou Mengge,Li Yonghua

Funder

Chinese Academy of Sciences

Publisher

Elsevier BV

Subject

Pollution,Waste Management and Disposal,Environmental Chemistry,Environmental Engineering

Reference96 articles.

1. Profile distribution and source identification of potentially toxic elements in North Nile Delta, Egypt;Abuzaid;Soil Sediment Contam.,2019

2. Cobalt hybrid catalysts in Fischer-Tropsch synthesis;Adeleke;Rev. Chem. Eng.,2020

3. Prediction of the concentration of antimony in agricultural soil using data fusion, terrain attributes combined with regression kriging;Agyeman;Environ. Pollut.,2023

4. An explainable machine learning framework for lung cancer hospital length of stay prediction;Alsinglawi;Sci. Rep.,2022

5. Identifying sources and transport routes of heavy metals in soil with different land uses around a smelting site by GIS based PCA and PMF;Anaman;Sci. Total Environ.,2022

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