has been cited by the following article(s):
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[1]
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Thinning intensity inhibits microbial metabolic limitation and promotes microbial carbon use efficiency in natural secondary forests in the Qinling Mountains
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Forest Ecology and …,
2024 |
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[2]
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Machine Intelligence in Africa: a survey
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arXiv preprint arXiv …,
2024 |
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[3]
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Digital exploration of selected heavy metals using Random Forest and a set of environmental covariates at the watershed scale
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Journal of Hazardous …,
2023 |
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[4]
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Fertilization as the most critical factor affecting yield response and agronomic efficiency of phosphorus in Chinese rice production: evidence from multi‐location field …
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Journal of the …,
2023 |
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[5]
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Effects of the Ratio of Substituting Mineral Fertilizers with Manure Nitrogen on Soil Properties and Vegetable Yields in China: A Meta-Analysis
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Plants,
2023 |
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[6]
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Machine learning-based prediction of toxic metals concentration in an acid mine drainage environment, northern Tunisia
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… Science and Pollution …,
2022 |
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[7]
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Multi-scale application of advanced ANN-MLP model for increasing the large-scale Improvement of digital data visualisation due to anomalous lithogenic and …
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Minerals,
2022 |
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[8]
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An insight into machine learning models era in simulating soil, water bodies and adsorption heavy metals: Review, challenges and solutions
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2021 |
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[9]
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What are the key factors affecting maize yield response to and agronomic efficiency of phosphorus fertilizer in China?
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2021 |
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[10]
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The assessment of spatial distribution of trace elements in soil and moss using artificial intelligence in the Bregalnica river basin, North Macedonia
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Mining and …,
2021 |
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[11]
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Digital Soil Mapping of Metals and Metalloids in Croplands Using Multiple Geospatial Data and Machine Learning, Implemented in Gee, for the Peruvian Mantaro …
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Vilchez, J Huamani, J Cruz… - Implemented in Gee
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[1]
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Modelling the distribution and transport of heavy metals on water and soil: a systematic review
International Journal of Environmental Science and Technology,
2026
DOI:10.1007/s13762-025-06868-6
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[2]
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The prediction of heavy metal contamination in groundwater using machine learning algorithms: a case study from the Harran Plain, a major agricultural irrigation area in Türkiye
Environmental Geochemistry and Health,
2025
DOI:10.1007/s10653-025-02644-0
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[3]
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Multi-Criteria Risk Assessment and Prediction of Heavy Metal Pollution of Soils Around Pb–Zn Artisanal Mining Hotspots in Southeastern Nigeria
Water, Air, & Soil Pollution,
2025
DOI:10.1007/s11270-025-08549-z
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[4]
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Multi-Scale Application of Advanced ANN-MLP Model for Increasing the Large-Scale Improvement of Digital Data Visualisation Due to Anomalous Lithogenic and Anthropogenic Elements Distribution
Minerals,
2022
DOI:10.3390/min12020174
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[5]
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Machine learning-based prediction of toxic metals concentration in an acid mine drainage environment, northern Tunisia
Environmental Science and Pollution Research,
2022
DOI:10.1007/s11356-022-21890-8
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