Identification of point source emission in river pollution incidents based on Bayesian inference and genetic algorithm: Inverse modeling, sensitivity, and uncertainty analysis-Reference-Cited by-同舟云学术

Identification of point source emission in river pollution incidents based on Bayesian inference and genetic algorithm: Inverse modeling, sensitivity, and uncertainty analysis

Published:2021-09 Issue: Volume:285 Page:117497
ISSN:0269-7491
Container-title:Environmental Pollution
language:en
Short-container-title:Environmental Pollution

Author:

Zhu Yinying^ORCID,Chen Zhi,Asif Zunaira

Publisher

Elsevier BV

Subject

Health, Toxicology and Mutagenesis,Pollution,Toxicology,General Medicine

Reference63 articles.

1. Source characterization of atmospheric releases using stochastic search and regularized gradient optimization;Addepalli;Inverse Prob. Sci. Eng.,2011

2. Recovering the release history of a groundwater contaminant using a non‐linear least‐squares method;Alapati;Hydrol. Process.,2000

3. Improving pollutant source characterization by better estimating wind direction with a genetic algorithm;Allen;Atmos. Environ.,2007

4. A hybrid simulation–optimization approach for solving the areal groundwater pollution source identification problems;Ayvaz;J. Hydrol.,2016

5. A General Probabilistic Framework for uncertainty and global sensitivity analysis of deterministic models: a hydrological case study;Baroni;Environ. Model. Software,2014

Cited by 23 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. Crucial time of emergency monitoring for reliable numerical pollution source identification;Water Research;2024-11

2. Safety risk assessment of shield tunneling under existing tunnels: A hybrid trapezoidal cloud model and Bayesian network approach;Tunnelling and Underground Space Technology;2024-10

3. Deep optimization of water quality index and positive matrix factorization models for water quality evaluation and pollution source apportionment using a random forest model;Environmental Pollution;2024-04

4. A DiffeRential Evolution Adaptive Metropolis (DREAM)-based inverse model for continuous release source identification in river pollution incidents: Quantitative evaluation and sensitivity analysis;Environmental Pollution;2024-04

5. Bayesian estimation and reconstruction of marine surface contaminant dispersion;Science of The Total Environment;2024-01