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You searched for: Subject term Monte Carlo method Remove constraint Subject term: Monte Carlo method Subject term Bayesian theory Remove constraint Subject term: Bayesian theory Subject term model uncertainty Remove constraint Subject term: model uncertainty
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1. Bayesian Approach to Probabilistic Design Space Characterization: A Nested Sampling Strategy

Author:
Kennedy P. Kusumo; Lucian Gomoescu; Radoslav Paulen; Salvador García Muñoz; Constantinos C. Pantelides; Nilay Shah; Benoît Chachuat
Source:
Industrial & engineering chemistry process design and development 2019 v.59 no.6 pp. 2396-2408
ISSN:
1520-5045
Subject:
Bayesian theory; Monte Carlo method; algorithms; artificial intelligence; case studies; computational methodology; dynamic models; manufacturing; model uncertainty; prediction; risk
Abstract:
... Quality by design in pharmaceutical manufacturing hinges on computational methods and tools that are capable of accurate quantitative prediction of the design space. This paper investigates Bayesian approaches to design space characterization, which determine a feasibility probability that can be used as a measure of reliability and risk by the practitioner. An adaptation of nested sampling—a Mont ...
DOI:
10.1021/acs.iecr.9b05006

2. Sensitivity and uncertainty analysis in agro-hydrological modelling of drip fertigated lettuce crops under Mediterranean conditions

Author:
E.M. Suárez-Rey; M. Gallardo; M. Romero-Gámez; C. Giménez; F.J. Rueda
Source:
Computers and electronics in agriculture 2019 v.162 pp. 630-650
ISSN:
0168-1699
Subject:
Bayesian theory; Monte Carlo method; biomass production; crop models; crops; decision making; environmental factors; fertigation; field experimentation; lettuce; microirrigation; model uncertainty; nitrogen balance; risk management; soil water; uncertainty analysis
Abstract:
... Most agro-hydrological modelling studies of fertigated crops published in the literature are based on classical model identification approaches, in which a single and optimal representation of the water/nitrogen balance and crop biomass production is sought, through the calibration of model parameters. Here, the concept of an optimal parameter set is rejected in favor of the concept of equifinalit ...
DOI:
10.1016/j.compag.2019.05.011

3. Towards Improving the Efficiency of Bayesian Model Averaging Analysis for Flow in Porous Media via the Probabilistic Collocation Method

Author:
Liang Xue; Cheng Dai; Yujuan Wu; Lei Wang
Source:
Water 2018 v.10 no.4 pp. -
ISSN:
2073-4441
Subject:
Bayesian theory; Monte Carlo method; groundwater; hydraulic conductivity; model uncertainty; models; porous media; response surface methodology; uncertainty analysis; variance
Abstract:
... The characterization of flow in subsurface porous media is associated with high uncertainty. To better quantify the uncertainty of groundwater systems, it is necessary to consider the model uncertainty. Multi-model uncertainty analysis can be performed in the Bayesian model averaging (BMA) framework. However, the BMA analysis via Monte Carlo method is time consuming because it requires many forwar ...
DOI:
10.3390/w10040412

4. Bayesian parameter inference for individual-based models using a Particle Markov Chain Monte Carlo method

Author:
Mira Kattwinkel; Peter Reichert
Source:
Environmental modelling & software 2017 v.87 pp. 110-119
ISSN:
1364-8152
Subject:
Bayesian theory; Markov chain; Monte Carlo method; algorithms; computer software; environmental models; model uncertainty; profits and margins; time series analysis
Abstract:
... Parameter estimation for agent-based and individual-based models (ABMs/IBMs) is often performed by manual tuning and model uncertainty assessment is often ignored. Bayesian inference can jointly address these issues. However, due to high computational requirements of these models and technical difficulties in applying Bayesian inference to stochastic models, the exploration of its application to A ...
DOI:
10.1016/j.envsoft.2016.11.001

5. Assessment of the value of groundwater age time-series for characterizing complex steady-state flow systems using a Bayesian approach

Author:
Arash Massoudieh; Sarah Leray; Jean-Raynald de Dreuzy
Source:
Applied geochemistry 2014 v.50 pp. 240-251
ISSN:
0883-2927
Subject:
Bayesian theory; Markov chain; Monte Carlo method; aquifers; chlorofluorocarbons; geochemistry; groundwater; model uncertainty; models; sulfur hexafluoride; time series analysis; tracer techniques; France
Abstract:
... In this work, the effectiveness of transient environmental tracer data in reducing the uncertainty associated with the inference of groundwater residence time distribution was evaluated. A Bayesian Markov Chain Monte Carlo method was used to infer the parameters of presumed residence time distribution forms—exponential and gamma—using concentrations of five tracers, including CFC-11, CFC-12, CFC-1 ...
DOI:
10.1016/j.apgeochem.2013.10.006

6. Lifetime PCB 153 bioaccumulation and pharmacokinetics in pilot whales: Bayesian population PBPK modeling and Markov chain Monte Carlo simulations

Author:
Liesbeth Weijs; Anthony C. Roach; Raymond S.H. Yang; Robin McDougall; Michael Lyons; Conrad Housand; Detlef Tibax; Therese Manning; John Chapman; Katelyn Edge; Adrian Covaci; Ronny Blust
Source:
Chemosphere 2014 v.94 pp. 91-96
ISSN:
0045-6535
Subject:
Bayesian theory; Markov chain; Monte Carlo method; bioaccumulation; blubber; data collection; mice; model uncertainty; models; pharmacokinetics; pollutants; polychlorinated biphenyls; prediction; probability distribution; rats; whales; wild animals; Tasmania
Abstract:
... Physiologically based pharmacokinetic (PBPK) models for wild animal populations such as marine mammals typically have a high degree of model uncertainty and variability due to the scarcity of information and the embryonic nature of this field. Parameters values used in marine mammals models are usually taken from other mammalian species (e.g. rats or mice) and might not be entirely suitable to pro ...
DOI:
10.1016/j.chemosphere.2013.09.019

7. Multimodel Bayesian analysis of data-worth applied to unsaturated fractured tuffs

Author:
Dan Lu; Ming Ye; Shlomo P. Neuman; Liang Xue
Source:
Advances in water resources 2012 v.35 no. pp. 69-82
ISSN:
0309-1708
Subject:
Bayesian theory; Monte Carlo method; model uncertainty; parameter uncertainty; permeability; risk; tuff; water resources; Arizona
Abstract:
... To manage water resource and environmental systems effectively requires suitable data. The worth of collecting such data depends on their potential benefit and cost, including the expected cost (risk) of failing to take an appropriate decision. Evaluating this risk calls for a probabilistic approach to data-worth assessment. Recently we [39] developed a multimodel approach to optimum value-of-info ...
DOI:
10.1016/j.advwatres.2011.10.007