Uncertainty models for stochastic optimization in renewable energy applications
… reviews the generic steps of stochastic optimizations in renewable energy applications, from
the modelling of the uncertainties … Furthermore, the benefits and drawbacks of the stochastic …
the modelling of the uncertainties … Furthermore, the benefits and drawbacks of the stochastic …
[HTML][HTML] A survey of uncertainty in deep neural networks
… s and a training data set \(\mathcal {D}\), the training of a neural network is a stochastic
process and therefore the resulting neural network \(f_\theta\) is based on a random variable, …
process and therefore the resulting neural network \(f_\theta\) is based on a random variable, …
Modern Monte Carlo methods for efficient uncertainty quantification and propagation: A survey
J Zhang - Wiley Interdisciplinary Reviews: Computational …, 2021 - Wiley Online Library
… simulate a random or stochastic simulation model. If the computational model is available,
the stochastic simulation … times, changing only the input random variable that is randomly …
the stochastic simulation … times, changing only the input random variable that is randomly …
Quantification of model uncertainty in RANS simulations: A review
H Xiao, P Cinnella - Progress in Aerospace Sciences, 2019 - Elsevier
… and structural uncertainties in turbulence models. We review recent literature on data-free
(uncertainty … It is also referred to as stochastic process when the index is time coordinate t. …
(uncertainty … It is also referred to as stochastic process when the index is time coordinate t. …
State-of-the-art techniques for modelling of uncertainties in active distribution network planning: A review
A Ehsan, Q Yang - Applied energy, 2019 - Elsevier
… accurate and efficient modelling of these uncertainties is … uncertainty modelling techniques
is reviewed, discussed, and categorised into the following: probabilistic techniques, stochastic …
is reviewed, discussed, and categorised into the following: probabilistic techniques, stochastic …
[HTML][HTML] Existing approaches and trends in uncertainty modelling and probabilistic stability analysis of power systems with renewable generation
… in this review include stochastic process, probabilistic simulation and uncertainty modelling.
… probability distributions has been thoroughly reviewed in this paper. Interactions, …
… probability distributions has been thoroughly reviewed in this paper. Interactions, …
[HTML][HTML] A review of uncertainty quantification in deep learning: Techniques, applications and challenges
… This study reviews recent advances in UQ methods used in deep learning, investigates
the application of these methods in reinforcement learning, and highlights the fundamental …
the application of these methods in reinforcement learning, and highlights the fundamental …
Recent trends in the modeling and quantification of non-probabilistic uncertainty
… of the field variable under the rather strict assumption of statistical homogeneity of the random
field. … This section provides a concise review of the basic interval arithmetical operations. …
field. … This section provides a concise review of the basic interval arithmetical operations. …
Uncertainty factors, methods, and solutions of closed-loop supply chain—A review for current situation and future prospects
H Peng, N Shen, H Liao, H Xue, Q Wang - Journal of Cleaner Production, 2020 - Elsevier
… process of the literature review, the author of this paper found that many scholars considered
a single uncertainty in … , we found that random uncertainty theory is used to study numerous …
a single uncertainty in … , we found that random uncertainty theory is used to study numerous …
A unified framework for stochastic optimization
WB Powell - European Journal of Operational Research, 2019 - Elsevier
… reviews the canonical models of these communities, and proposes a universal modeling …
Let W 1 , W 2 , … , W t , … represent a stochastic process that might describe stock prices, …
Let W 1 , W 2 , … , W t , … represent a stochastic process that might describe stock prices, …