18 Key responses of the parameter estimation modeling
Modeling and estimating uncertainty in parameter estimation
... estimated parameter as a random variable with unknown distribution, we conceptually reformulate the deterministic parameter estimation problem into a problem of estimation of a random variable ...
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Modeling and parameter estimation for an imperfectly clamped plate
... 2 Modeling Equations The derivation which follows will be for a circular plate although analogous arguments can be used for plates having other geometries, as well as shells and ...
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Cardiovascular and Respiratory Regulation, Modeling and Parameter Estimation
... nominal parameter values during the op- timization ...identifiable parameter, while the cerebrovascular resis- tance R acp was grouped with parameters to be kept ...the parameter A acp only appears ...
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Determine measurement set for parameter estimation in biological systems modeling
... for parameter estimation, in which the parameter searching space in all simulations were set to be ...estimated parameter values are given in Table ...the parameter values, among them ...
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Surface Parameter Estimation by Inverse Modeling of Ground Penetrating Radar
... standard modeling method and inversion schemes to realize a SFCW ...GPR modeling schemes published by the researchers ...parameters estimation as compared to other modeling methods for a ...
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Modeling and Bayesian parameter estimation for shape memory alloy bending actuators
... ABSTRACT In this paper, we employ a homogenized energy model (HEM) for shape memory alloy (SMA) bending actuators. Additionally, we utilize a Bayesian method for quantifying parameter uncertainty. The system ...
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Modeling the East Coast Akalat Population: Model Comparison and Parameter Estimation
... When working with ecological data, one often loses the control that laboratory experimental data offers and mathematicians and statisticians hope for. One of the largest and most unforeseen dif- ficulties was the problem ...
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HESS Opinions: Advocating process modeling and de emphasizing parameter estimation
... sible parameter values (that would be impossible to attempt manually), and can provide useful support to model diagnos- tic ...best parameter estimate is physically unrealistic, one may conclude that the ...
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Input force estimation accounting for modeling errors and noise in responses
... force estimation, regularization technique, total least squares, ill-posed problem, inverse problem 1 Introduction Accurate determination of dynamic input forces experienced during operation of machines and ...
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Modeling the vertical soil organic matter profile using Bayesian parameter estimation
... with the organic carbon measurements, we believe this iso- tope holds value as a SOM tracer. Our study illustrates the difficulties with explaining the vertical SOM profile caused by the convolution of several ...
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Sensitivity analysis and parameter estimation for distributed hydrological modeling: potential of variational methods
... the parameter and observa- tions spaces brings out relevant features of the rainfall-runoff ...for parameter values leading to an acceptable fit to the available observations, the analysis should be carried ...
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Sensitivity analysis and parameter estimation for the distributed modeling of infiltration excess overland flow
... the parameter estimation experiments carried out in the previous sec- 20 tion, a more complex virtual hydrological reality was used for the generation of the synthetic discharge ...
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Application of ensemble transform data assimilation methods for parameter estimation in reservoir modeling
... accurate estimation of subsurface geological properties like permeability and porosity is essential for many fields, especially where such predictions can have a large economic or environmental impact, for ...
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Contributions to measurement-based dynamic MIMO channel modeling and propagation parameter estimation
... deterministic modeling approach is so- called ray tracing (RT) [18, 42, ...RT modeling is best applicable in man made environments, where also the structural database can be assumed to ...
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Adaptive Smoothing Parameter in Kernel Density Estimation and Parameter Estimation in Normal Mixture Distributions
... Density Estimation when a dataset is available, the distribution in which the data set is derived from is a key ...parametric estimation, a distribution is postulated and then the parameters are ...
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Parameter estimation for dynamical systems
... the key issue of robustness, we go on to establish conditions that ensure that the desired properties of the solution to the inverse problem are maintained on an open neighborhood of the given ...real ...
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Parameter Estimation for LDA Frames
... The question, however, is how to make the sam- pled frames shared between different lexical units. We propose to generate base distributions of the DPs from GEM distribution (Pitman, 2002) τ with concentration ...
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Parameter Estimation of Exciation Systems
... 4. 18 Final terminal output of generator when estimating AC1A excitation using DGN starting from P L The history in Table 6 tells us the method converged very slowly and terminated due to maximum ...the ...
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Curve Fitting and Parameter Estimation
... 1.5 Parameter Estimation Directly from Differential Equations In modeling a new phenomenon, we often find that we can write down a differential equation that models the phenomenon, but we cannot ...
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A PDE-based methodology for modeling, parameter estimation and feedback control in structural and structural acoustic systems
... PDE-based parameter estimation and feedback control strategy for structural and structural acoustic systems has been ...After modeling the structure by thin plate equations with piecewise constant ...
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