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Page 1
Application of artificial intelligence deep learning in numerical simulation of seawater intrusion.
Environ Sci Pollut Res Int. 2021 Oct;28(38):54096-54104. doi: 10.1007/s11356-021-13680-5. Epub 2021 May 27.
Environ Sci Pollut Res Int. 2021.
PMID: 34046828
Multiobjective optimization of the groundwater exploitation layout in coastal areas based on multiple surrogate models.
Fan Y, Lu W, Miao T, Li J, Lin J.
Fan Y, et al. Among authors: miao t.
Environ Sci Pollut Res Int. 2020 Jun;27(16):19561-19576. doi: 10.1007/s11356-020-08367-2. Epub 2020 Mar 26.
Environ Sci Pollut Res Int. 2020.
PMID: 32215802
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The application of 0-1 mixed integer nonlinear programming optimization model based on a surrogate model to identify the groundwater pollution source.
Guo JY, Lu WX, Yang QC, Miao TS.
Guo JY, et al.
J Contam Hydrol. 2019 Jan;220:18-25. doi: 10.1016/j.jconhyd.2018.11.005. Epub 2018 Nov 19.
J Contam Hydrol. 2019.
PMID: 30473396
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Optimal design of groundwater pollution monitoring network based on the SVR surrogate model under uncertainty.
Fan Y, Lu W, Miao T, An Y, Li J, Luo J.
Fan Y, et al. Among authors: miao t.
Environ Sci Pollut Res Int. 2020 Jul;27(19):24090-24102. doi: 10.1007/s11356-020-08758-5. Epub 2020 Apr 17.
Environ Sci Pollut Res Int. 2020.
PMID: 32304051
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Modeling and uncertainty analysis of seawater intrusion based on surrogate models.
Miao T, Lu W, Guo J, Lin J, Fan Y.
Miao T, et al.
Environ Sci Pollut Res Int. 2019 Sep;26(25):26015-26025. doi: 10.1007/s11356-019-05799-3. Epub 2019 Jul 4.
Environ Sci Pollut Res Int. 2019.
PMID: 31273667
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Application of ensemble surrogates and adaptive sequential sampling to optimal groundwater remediation design at DNAPLs-contaminated sites.
Ouyang Q, Lu W, Miao T, Deng W, Jiang C, Luo J.
Ouyang Q, et al. Among authors: miao t.
J Contam Hydrol. 2017 Dec;207:31-38. doi: 10.1016/j.jconhyd.2017.10.007. Epub 2017 Nov 6.
J Contam Hydrol. 2017.
PMID: 29128132
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