Progress in accurate chemical kinetic modeling, simulations, and parameter estimation for heterogeneous catalysis
Chemical kinetic modeling in heterogeneous catalysis is advancing in its ability to provide
qualitatively or even quantitatively accurate prediction of real-world behavior because of …
qualitatively or even quantitatively accurate prediction of real-world behavior because of …
Combining probabilistic load forecasts
Probabilistic load forecasts provide comprehensive information about future load
uncertainties. In recent years, many methodologies and techniques have been proposed for …
uncertainties. In recent years, many methodologies and techniques have been proposed for …
Soil organic carbon mapping using multispectral remote sensing data: Prediction ability of data with different spatial and spectral resolutions
The image spectral data, particularly hyperspectral data, has been proven as an efficient
data source for mapping of the spatial variability of soil organic carbon (SOC). Multispectral …
data source for mapping of the spatial variability of soil organic carbon (SOC). Multispectral …
[HTML][HTML] Load probability density forecasting by transforming and combining quantile forecasts
Compared with traditional deterministic load forecasting, probabilistic load forecasting (PLF)
help us understand the potential risks in the power system operation by providing more …
help us understand the potential risks in the power system operation by providing more …
Unified framework and survey for model verification, validation and uncertainty quantification
S Riedmaier, B Danquah, B Schick… - Archives of Computational …, 2021 - Springer
Simulation is becoming increasingly important in the development, testing and approval
process in many areas of engineering, ranging from finite element models to highly complex …
process in many areas of engineering, ranging from finite element models to highly complex …
Model validation and scenario selection for virtual-based homologation of automated vehicles
Due to the rapid progress in the development of automated vehicles over the last decade,
their market entry is getting closer. One of the remaining challenges is the safety assessment …
their market entry is getting closer. One of the remaining challenges is the safety assessment …
Identifying active sites of the water–gas shift reaction over titania supported platinum catalysts under uncertainty
A comprehensive uncertainty quantification framework has been developed for integrating
computational and experimental kinetic data and to identify active sites and reaction …
computational and experimental kinetic data and to identify active sites and reaction …
Validating predictions of unobserved quantities
TA Oliver, G Terejanu, CS Simmons… - Computer Methods in …, 2015 - Elsevier
The ultimate purpose of most computational models is to make predictions, commonly in
support of some decision-making process (eg, for design or operation of some system). The …
support of some decision-making process (eg, for design or operation of some system). The …
Inverse uncertainty quantification using the modular Bayesian approach based on Gaussian Process, Part 2: Application to TRACE
Abstract Inverse Uncertainty Quantification (UQ) is a process to quantify the uncertainties in
random input parameters while achieving consistency between code simulations and …
random input parameters while achieving consistency between code simulations and …
[HTML][HTML] Stochastic resonance in the recovery of signal from agent price expectations
SD Silver, M Raseta, A Bazarova - Chaos, Solitons & Fractals, 2023 - Elsevier
Contributions that noise can make to the objective of detecting signal in agent expectations
for price in financial markets are examined. Although contrary to most assumptions on …
for price in financial markets are examined. Although contrary to most assumptions on …