Groundwater contamination source estimation based on a refined particle filter associated with a deep residual neural network surrogate
Author:
Publisher
Springer Science and Business Media LLC
Subject
Earth and Planetary Sciences (miscellaneous),Water Science and Technology
Link
https://link.springer.com/content/pdf/10.1007/s10040-022-02454-z.pdf
Reference50 articles.
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2. Arulampalam MS, Maskell S, Gordon N, Clapp T (2002) A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking. IEEE Trans Signal Process 50:174–188. https://doi.org/10.1109/78.978374
3. Asher MJ, Croke BFW, Jakeman AJ, Peeters LJM (2015) A review of surrogate models and their application to groundwater modeling. Water Resour Res 51:5957–5973. https://doi.org/10.1002/2015wr016967
4. Assumaning GA, Chang S-Y(2016) Application of sequential data-assimilation techniques in groundwater contaminant transport modeling. J Environ Eng-ASCE:142. https://doi.org/10.1061/(asce)ee.1943-7870.0001034
5. Ayvaz MT (2010) A linked simulation-optimization model for solving the unknown groundwater pollution source identification problems. J Contam Hydrol 117:46–59. https://doi.org/10.1016/j.jconhyd.2010.06.004
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