Uncertainty reduction and characterization for complex environmental fate and transport models: An empirical Bayesian framework incorporating the stochastic response surface method-Reference-Cited by-同舟云学术

Uncertainty reduction and characterization for complex environmental fate and transport models: An empirical Bayesian framework incorporating the stochastic response surface method

Published:2003-12 Issue:12 Volume:39 Page:
ISSN:0043-1397
Container-title:Water Resources Research
language:en
Short-container-title:Water Resour. Res.

Author:

Balakrishnan Suhrid¹²,Roy Amit¹,Ierapetritou Marianthi G.²,Flach Gregory P.³,Georgopoulos Panos G.¹²

Affiliation:

1. Environmental and Occupational Health Sciences Institute; University of Medicine and Dentistry of New Jersey-R.W. Johnson Medical School and Rutgers University; Piscataway New Jersey USA

2. Department of Chemical and Biochemical Engineering; Rutgers University; Piscataway New Jersey USA

3. Savannah River Technology Center; Savannah River Site; Aiken South Carolina USA

Publisher

American Geophysical Union (AGU)

Subject

Water Science and Technology

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1029/2002WR001810/fullpdf

Reference27 articles.

1. Updating uncertainty in an integrated risk assessment: Conceptual framework and methods;Brand;Risk Anal.,1995

2. General methods for monitoring convergence of iterative simulations;Brooks;J. Comput. Graphical Stat.,1998

3. Bayesian maximum entropy analysis and mapping: A farewell to kriging estimators?;Christakos;Math. Geol.,1998

4. Bayesian prediction of deterministic functions, with applications to the design and analysis of computer experiments;Currin;J. Am. Stat. Assoc.,1991

Cited by 44 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. Monte Carlo Methods for Industry 4.0 Applications;2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC);2022-10-09

2. A transport-based multifidelity preconditioner for Markov chain Monte Carlo;Advances in Computational Mathematics;2019-07-03

3. Development of Probabilistic Dam Breach Model Using Bayesian Inference;Water Resources Research;2018-07

4. The Earth Resources Challenge;Quantifying Uncertainty in Subsurface Systems;2018-06-07

5. On uncertainty quantification in hydrogeology and hydrogeophysics;Advances in Water Resources;2017-12