Comparison of surrogate models with different methods in groundwater remediation process
Author:
Publisher
Springer Science and Business Media LLC
Subject
General Earth and Planetary Sciences
Link
http://link.springer.com/content/pdf/10.1007/s12040-014-0494-0.pdf
Reference51 articles.
1. Ahlfeld D P, Mulvey J M and Pinder G F 1988 Contaminated groundwater remediation design using simulation, optimization, and sensitivity theory 2. Analysis of a field site; Water Resour. Res. 24 443–452.
2. Arndt O, Barth T, Freisleben B and Grauer M 2005 Approximating a finite element model by neural network prediction for facility optimization in groundwater engineering; European J. Oper. Res. 166 769–781.
3. Baddari K, Aïfa T, Djarfour N and Ferahtia J 2009 Application of a radial basis function artificial neural network to seismic data inversion; Comput. Geosci. 35 2338–2344.
4. Behzadian K, Kapelan Z, Savic D and Ardeshir A 2009 Stochastic sampling design using a multi-objective genetic algorithm and adaptive neural networks; Environ. Modell. Softw. 24 530–541.
5. Bhattarai M 2006 A numerical modeling study of surfactant enhanced mobilization of residual LNAPL using UTCHEM; Southern Illinois University Carbondale, Carbondale, USA.
Cited by 48 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. Application of observed data denoising based on variational mode decomposition in groundwater pollution source recognition;Science of The Total Environment;2024-10
2. AOK‐ES: Adaptive optimized Kriging combining efficient sampling for structural reliability analysis;Quality and Reliability Engineering International;2024-01-23
3. A construction strategy of Kriging surrogate model based on Rosenblatt transformation of associated random variables and its application in groundwater remediation;Journal of Environmental Management;2024-01
4. Review of machine learning-based surrogate models of groundwater contaminant modeling;Environmental Research;2023-12
5. Groundwater pollution source identification using Metropolis-Hasting algorithm combined with Kalman filter algorithm;Journal of Hydrology;2023-11
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