Uncertainties in model parameters significantly impact long-term forest sector projections, with supply and demand elasticities dominating the uncertainty.

Effects of parameter and data uncertainty on long-term projections in a model of the global forest sector

Temperature uncertainty dominates model parameter settings and initial condition uncertainty in malaria simulations in highland locations, with initial condition uncertainty playing a lesser role after two years.

Uncertainty in malaria simulations in the highlands of Kenya: Relative contributions of model parameter setting, driving climate and initial condition errors

Operative flood forecasting systems in complex topographic areas benefit from superposing meteorological forcing, initial conditions, and hydrological model uncertainties, with the latter being less pronounced.

Superposition of three sources of uncertainties in operational flood forecasting chains

The HIV-1 infection model with uncertain initial data can be stabilized using the fuzzy Laplace Adomian decomposition method, providing numerical results for various fractional orders.

Study of the Fractional-Order HIV-1 Infection Model with Uncertainty in Initial Data

Physical parameterization uncertainty is greater for short-term wind speed predictions, but initial conditions uncertainty also plays a significant role in complex terrain, especially during thermal inversion conditions.

Characterization of Spread in a Mesoscale Ensemble Prediction System: Multiphysics versus Initial Conditions

This paper presents a new method for determining the supremum and infimum of time response in structures with bounded parameters and interval initial conditions, providing more accurate results and addressing uncertainties in initial conditions.

The time response of structures with bounded parameters and interval initial conditions

Uncertainty in input and parameter values increases model variance, but adjusted parameters decrease this effect, making it more useful for predicting sugar accumulation in fruit.

Effect of uncertainty in input and parameter values on model prediction error

Uncertainty in initial ice roughness and coefficient of heat exchange between air and ice significantly affects ice processes simulation, affecting water stage and discharge variations and ice cover formation.

Effect of uncertain parameters on ice processes simulation

The prediction uncertainty in numerical models of groundwater flow is influenced by the magnitude of parameter uncertainty and the sensitivity of predictions to parameters.

First order analysis of uncertainty in numerical models of groundwater flow part: 1. Mathematical development

Model-based analysis in healthcare decision-making benefits from examining and reporting uncertainty, with expected value of perfect information being the most appropriate presentational technique for decision uncertainty.

Model Parameter Estimation and Uncertainty Analysis

The proposed models and algorithms significantly reduce solution time in preliminary design tasks with epistemic uncertainty, compared to Monte Carlo methods.

Preliminary Design With the Epistemic Uncertainty of Parameters

Parameter uncertainty significantly affects impulse response analysis in nonlinear models, with various functions varying in their treatment of uncertainty.

Parameter uncertainty and impulse response analysis

UncertainSCI is a lightweight, open-source software tool that accurately quantifies parametric variability and uncertainty in biomedical simulations, enabling users to leverage existing software libraries and suites.

UncertainSCI: Uncertainty quantification for computational models in biomedicine and bioengineering

Quantifying hydraulic parameter uncertainties can improve reliability-based design and decision-making in hydraulic engineering.

Uncertainty of Hydraulic Parameters

The global sensitivity indicator effectively measures the influence of input uncertainty on the entire output distribution in risk assessment models, offering a more comprehensive approach.

A new uncertainty importance measure

The IPREM method effectively quantifies input parameter uncertainties in thermal-hydraulic codes, supporting the validity of reflood-related models in RELAP5 and CATHARE2 codes.

Development and assessment of a method for evaluating uncertainty of input parameters

Uncertainties in conceptual models are more significant than parameter uncertainties in groundwater models, as they impact predictive simulations considering data types extrapolated from calibration data types.

Model uncertainty--parameter uncertainty versus conceptual models.

This paper presents an optimal robust linear filter for convex bounded parameter uncertainty, using linear matrix inequality solvers for better error variance minimization compared to previous results.

Optimal linear filtering under parameter uncertainty

This paper presents a theoretical approach to evaluate uncertainty in photovoltaic cell parameter estimation using data from panel manufacturers, measured environmental parameters, and semiempirical equations.

Uncertainty Analysis in Photovoltaic Cell Parameter Estimation

The method of moments effectively estimates parameters in uncertain differential equations, providing accurate solutions to the problem in various applications.

Parameter estimation in uncertain differential equations

how do parameter uncertainty and initial conditions uncertainty affect each other?

Some studies suggest that parameter uncertainty significantly impacts model outcomes, while other studies indicate that initial conditions uncertainty also plays a crucial role, particularly in complex or specific scenarios.