Data prediction of soil heavy metal content by deep composite model-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

Data prediction of soil heavy metal content by deep composite model

Published:2020-10-14 Issue:1 Volume:21 Page:487-498
ISSN:1439-0108
Container-title:Journal of Soils and Sediments
language:en
Short-container-title:J Soils Sediments

Author:

Cao Wenqi,Zhang Cong^ORCID

Funder

National Nature Science Foundation of China

Major Technical Innovation Projects of Hubei Province

Natural Science Foundation of Hubei Province of China

National Science Fund for Youth of Hubei Province of China

Publisher

Springer Science and Business Media LLC

Subject

Stratigraphy,Earth-Surface Processes

Link

https://link.springer.com/content/pdf/10.1007/s11368-020-02793-y.pdf

Reference35 articles.

1. Alexandridis A, Chondrodima E, Sarimveis H (2013) Radial basis function network training using a nonsymmetric partition of the input space and particle swarm optimization. IEEE Trans Neural Networks Learn Syst 24(2):219–230

2. Babu GS, Suresh S (2013) Sequential projection-based metacognitive learning in a radial basis function network for classification problems. IEEE Trans Neural Networks Learn Syst 24(2):194–206

3. Chander K, Dyckmans J, Joergensen R, Meyer B (2001) Different sources of heavy metals and their long-term effects on soil microbial properties. Biol Fertil Soils 34(4):241–247

4. Chatterjee A, Siarry P (2011) Nonlinear inertia weight variation for dynamic adaptation in particle swarm optimization. Comput Oper Res 33(3):859–871

5. Cheng R, Jin Y (2014) A competitive swarm optimizer for large scale optimization. IEEE Trans Cybern 45(2):191–204

Cited by 6 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Comparative analysis of different machine learning algorithms for predicting trace metal concentrations in soils under intensive paddy cultivation;Computers and Electronics in Agriculture;2024-04

2. Source-specific probabilistic contamination risk and health risk assessment of soil heavy metals in a typical ancient mining area;Science of The Total Environment;2024-01

3. Spatial prediction of soil contamination based on machine learning: a review;Frontiers of Environmental Science & Engineering;2023-02-17

4. Risk Assessment of Agricultural Soil Heavy Metal Pollution Under the Hybrid Intelligent Evaluation Model;IEEE Access;2023

5. A two-point machine learning method for the spatial prediction of soil pollution;International Journal of Applied Earth Observation and Geoinformation;2022-04

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