Results 331 to 340 of about 8,393,375 (379)
Some of the next articles are maybe not open access.
Chemical Engineering Science, 1998
Abstract Mathematical models are of widespread usage for simulating process behavior, designing new processes and equipment and, in a more general sense, decision making. However, as model parameters are uncertain, due to model inaccuracies and experimental errors, all model results are subject to uncertainties.
openaire +2 more sources
Abstract Mathematical models are of widespread usage for simulating process behavior, designing new processes and equipment and, in a more general sense, decision making. However, as model parameters are uncertain, due to model inaccuracies and experimental errors, all model results are subject to uncertainties.
openaire +2 more sources
Linear and Nonlinear Fault Location in Smart Distribution Network Under Line Parameter Uncertainty
IEEE Transactions on Industrial Informatics, 2021Hamid Mirshekali +4 more
semanticscholar +1 more source
A Premium for Parameter Uncertainty in Equities
SSRN Electronic Journal, 2014The literature on the effects of parameter uncertainty on optimal portfolio choice suggests the existence of a premium for parameter uncertainty in asset returns. We use a simple extension to classical mean-variance portfolio optimization and devise a robust strategy to benefit from such a premium.
Alex Weissensteiner, Michael Hanke
openaire +2 more sources
The analogy between parameter uncertainty and parameter changes
Economics Letters, 1980Abstract The approximate relationship between the responses to the imposition of slight parameter uncertainty and to parameter changes under certainty is developed for a limited range of models. The analysis is applied to a number of examples in the theory of the firm.
openaire +2 more sources
Goodness of Fit and Parameter Uncertainty
2013After calculating the best-fit values of model parameters, it is necessary to determine whether the model is actually a correct description of the data, even when we use the best possible values for the free parameters. In fact, only when the model is acceptable are best-fit parameters meaningful. The acceptability of a model is typically addressed via
openaire +2 more sources
Pulse parameter uncertainty analysis
Metrologia, 2002A detailed uncertainty analysis is presented for the pulse parameter measurement service of the National Institute of Standards and Technology (NIST, USA). It relates to the new pulse parameter measurement and extraction processes. Uncertainties for pulse amplitude, transition duration, overshoot and undershoot (preshoot) are given.
Nicholas G. Paulter, Donald R. Larson
openaire +2 more sources
Parameter Uncertainty Analysis of Surface Flow and Sediment Yield in the Huolin Basin, China
, 2014Growing concerns have been given to parameter uncertainty in hydrological modeling because of the associated effects on water resource management. In this study two uncertainty analysis methods, the sequential uncertainty fitting algorithm (SUFI-2) and ...
Chen-Li Xue, Bing Chen, Hongjing Wu
semanticscholar +1 more source
Structural Dynamics with Parameter Uncertainties
Applied Mechanics Reviews, 1987The treatment of structural parameters as random variables has been the subject of structural dynamicists and designers for many years. Several problems have been involved during the last few decades and resulted in new theorems and interesting phenomena.
openaire +2 more sources
Effects of Orbital Parameter Uncertainties
Journal of Guidance, Control, and Dynamics, 2005A number of important space flight mechanics problems require accurate uncertainty estimates of the position and velocity of an orbiting object. The lack of information might simply derive from a tracking error or from a propagation error, and in many cases it can be of a significant magnitude to the extent that many objects orbiting around our planet ...
openaire +2 more sources
Interval forecasts and parameter uncertainty
Journal of Econometrics, 2006Forecast intervals generalize point forecasts to represent and incorporate uncertainty. Forecast intervals calculated from dynamic models typically sidestep the issue of parameter estimation. This paper shows how to construct asymptotic forecast intervals which incorporate the uncertainty due to parameter estimation.
openaire +2 more sources