Machine learning-based prediction of cadmium pollution in topsoil and identification of critical driving factors in a mining area-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

Machine learning-based prediction of cadmium pollution in topsoil and identification of critical driving factors in a mining area

Published:2024-07-13 Issue:9 Volume:46 Page:
ISSN:0269-4042
Container-title:Environmental Geochemistry and Health
language:en
Short-container-title:Environ Geochem Health

Author:

Li Cheng,Jiang Zhongcheng,Li Wenli,Yu Tao,Wu Xiangke,Hu Zhaoxin,Yang Yeyu,Yang Zhongfang,Xu Haofan,Zhang Wenping,Zhang Wenjie,Ye Zongda

Funder

Open project of Technical Innovation Center of Mine Geological Environmental Restoration Engineering in Southern Karst Area

Basic Scientific Research Projects of Institute of Karst Geology, CAGS

Postdoctoral Fellowship Program of CPSF

Guangxi Science and Technology Program

National Natural Science Foundation of China

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s10653-024-02087-z.pdf

Reference95 articles.

1. Abiodun, O. I., Jantan, A., Omolara, A. E., Dada, K. V., Mohamed, N. A., & Arshad, H. (2018). State-of-the-art in artificial neural network applications: A survey. Heliyon, 4, e00938.

2. Ai, J. Y., Zhong, N. N., George, S. C., Zhang, Y., Yao, L. P., & Wang, T. G. (2020). Evolution of paleo-weathering during the late Neoproterozoic in South China: Implications for paleoclimatic conditions and organic carbon burial. Palaeogeography, Palaeoclimatology, Palaeoecology, 555, 109843. https://doi.org/10.1016/j.palaeo.2020.109843

3. Behrens, T., MacMillan, R. A., Viscarra Rossel, R. A., Schmidt, K., & Lee, J. (2019). Teleconnections in spatial modelling. Geoderma, 354, 113854. https://doi.org/10.1016/j.geoderma.2019.07.012

4. Bhagat, S. K., Tung, T. M., & Yaseen, Z. M. (2020). Development of artificial intelligence for modeling wastewater heavy metal removal: State of the art, application assessment and possible future research. Journal of Cleaner Production, 250, 119473. https://doi.org/10.1016/j.jclepro.2019.119473

5. Blanco, C. M. G., Gomez, V. M. B., Crespo, P., & Ließ, M. (2018). Spatial prediction of soil water retention in a Paramo landscape: Methodological insight into machine learning using random forest. Geoderma, 316, 100–114. https://doi.org/10.1016/j.geoderma.2017.12.002

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号京ICP备18003416号-3