scholarly journals Uncovering the effects of heterogeneity and parameter sensitivity on within-host dynamics of disease: malaria as a case study

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Shade Horn ◽  
Jacky L. Snoep ◽  
David D. van Niekerk
Keyword(s):  
Disease Model ◽  
Robustness Analysis ◽  
Model Parameters ◽  
Local Sensitivity ◽  
Model Predictions ◽  
Weak Points ◽  
Determination Of Parameters ◽  
Associated Variables

Abstract Background The fidelity and reliability of disease model predictions depend on accurate and precise descriptions of processes and determination of parameters. Various models exist to describe within-host dynamics during malaria infection but there is a shortage of clinical data that can be used to quantitatively validate them and establish confidence in their predictions. In addition, model parameters often contain a degree of uncertainty and show variations between individuals, potentially undermining the reliability of model predictions. In this study models were reproduced and analysed by means of robustness, uncertainty, local sensitivity and local sensitivity robustness analysis to establish confidence in their predictions. Results Components of the immune system are responsible for the most uncertainty in model outputs, while disease associated variables showed the greatest sensitivity for these components. All models showed a comparable degree of robustness but displayed different ranges in their predictions. In these different ranges, sensitivities were well-preserved in three of the four models. Conclusion Analyses of the effects of parameter variations in models can provide a comparative tool for the evaluation of model predictions. In addition, it can assist in uncovering model weak points and, in the case of disease models, be used to identify possible points for therapeutic intervention.

scholarly journals The Effect of the Size of Traffic Analysis Zones on the Quality of Transport Demand Forecasts and Travel Assignments

2018 ◽  
Author(s):  
Mehmet Fatih Altan ◽  
Yunus Emre Ayözen
Keyword(s):  
Regression Model ◽  
Traffic Analysis ◽  
Model Parameters ◽  
The Public ◽  
Employment Density ◽  
Exponential Regression Model ◽  
Demand Forecasts

In this work we have studied the selection criteria for traffic analysis zones and the effects of their size and number on the model’s forecasting capabilities. To do so we have focused on the corridor of İstanbul’s Kadıköy-Kartal Metro Line and evaluated the consistency of demand forecasts and travel assignments versus actual measurements under different sizes of the Traffic Analysis Zones (TAZ). Significant improvements in model accuracy were observed by decreasing the zone size. Specifically, studying the public transport network assignments for the metro line when increasing the number of traffic analysis zones from 540 to 1,788 the root mean square error (RMSE) of forecasted vs. actual station-based counts was reduced by 23%. Subsequently, the study used population density and employment density as independent variables for the determination of the optimal radius for the 1,788 zone area, and applied an exponential regression model. Appropriate model parameters were derived for the above case study. The regression model resulted in R2 values over 0.62.

Study on Statistical Damage Softening Constitutive Model and Determination of Parameters for Rock Based on Lognormal Distribution

2011 ◽  
Vol 69 ◽  
pp. 33-38
Author(s):  
Jian Hua Wen ◽  
Cui Ying Zhou ◽  
Li Huang ◽  
Ye Cheng ◽  
Lin Chong Huang ◽  
...  
Keyword(s):  
Constitutive Model ◽  
Lognormal Distribution ◽  
Strain Softening ◽  
Model Parameters ◽  
Kolmogorov Smirnov ◽  
Random Distributions ◽  
Determination Of Parameters ◽  
Smirnov Test ◽  
Statistical Damage

Based on the property that micro-cells strength is consistent with lognormal distribution function, this paper presented a new statistical damage softening constitutive model simulating the full process of strain softening for rock. Through discussing the characteristics of random distributions for rock micro-cells strength, lognormal distribution assumption is tested by Kolmogorov-Smirnov test in statistics, and the reasonable method of geometry boundary condition is selected to determine model parameters that can be easily applied to the situations under different complex conditions. Gabbro experiment comparative analyses show that the new damage softening constitutive model is rational and convenient in engineering.

scholarly journals An approach to identify time consistent model parameters: sub-period calibration

2013 ◽  
Vol 17 (1) ◽  
pp. 149-161 ◽  
Author(s):  
S. Gharari ◽  
M. Hrachowitz ◽  
F. Fenicia ◽  
H. H. G. Savenije
Keyword(s):  
Model Performance ◽  
Realistic Model ◽  
Parameter Estimates ◽  
Model Parameters ◽  
New Approach ◽  
Consistent Model ◽  
Set Up ◽  
Consistent Parameter

Abstract. Conceptual hydrological models rely on calibration for the identification of their parameters. As these models are typically designed to reflect real catchment processes, a key objective of an appropriate calibration strategy is the determination of parameter sets that reflect a "realistic" model behavior. Previous studies have shown that parameter estimates for different calibration periods can be significantly different. This questions model transposability in time, which is one of the key conditions for the set-up of a "realistic" model. This paper presents a new approach that selects parameter sets that provide a consistent model performance in time. The approach consists of testing model performance in different periods, and selecting parameter sets that are as close as possible to the optimum of each individual sub-period. While aiding model calibration, the approach is also useful as a diagnostic tool, illustrating tradeoffs in the identification of time-consistent parameter sets. The approach is applied to a case study in Luxembourg using the HyMod hydrological model as an example.

scholarly journals Determination of parameters of a viscous-cohesive fracture model by inverse analysis

2015 ◽  
Vol 8 (5) ◽  
pp. 669-706 ◽  
Author(s):  
F. L. Gea dos Santos ◽  
J. L. A. O. Sousa
Keyword(s):  
Inverse Analysis ◽  
Fracture Process ◽  
Loading Rate ◽  
Process Zone ◽  
High Strength ◽  
Model Parameters ◽  
Cohesive Fracture ◽  
Cohesive Model ◽  
Determination Of Parameters

ABSTRACTThe quasi-brittle, loading rate dependent behaviour of the concrete, characterized by a fracture process zone (FPZ) ahead of the crack front, can be described through a viscous-cohesive model. In this paper, a viscous cohesive model proposed in a former paper is evaluated for a group of high strength concrete beams loaded at rates from 10-5 mm/s to 10+1 mm/s. A software has been developed to enable the automatic determination of the viscous-cohesive model parameters through inverse analysis on load-versus loading-point displacement (P-d) from threepoint bend tests on notched prismatic specimens. The strategy allowed the sensitivity analysis of the parameters related to viscous behaviour. The analysis of results shows that the formerly proposed model can be improved for a better simulation of the loading rate dependence on the cohesive fracture process.

3D Linear Identification of Mechanical Joint Using FRF Decoupling and Inverse Structural Modification Methods

2021 ◽  
Author(s):  
Hossein Soleimani ◽  
Ender Cigeroglu ◽  
H. Nevzat Özgüven
Keyword(s):  
Structural Modification ◽  
Model Parameters ◽  
Engineering Structures ◽  
Bolted Connection ◽  
Decoupling Method ◽  
Beam Elements ◽  
Method Formulation ◽  
Joint Parameters

Abstract Mechanical connections such as bolts and rivets are inevitable in most engineering structures and may significantly affect the dynamic behavior of the structures. Therefore, modeling a joint simply and accurately is essential for assembled structures. On the other hand, the most important step is the determination of these joint model parameters which will be used in the calculation of dynamic response of assembled structures. For this purpose, in this paper, FRF Decoupling Method (FRF-DM), proposed in an earlier study for bolted beam connections is extended in two ways: Firstly, the bolt model proposed for 2D beam elements is extended to 3D finite element models of structural systems, and thus the dynamics of a bolted connection is modeled as an equivalent 6 × 6 complex stiffness matrix including linear and torsional stiffnesses. Secondly, FRF-DM is extended to include measurements at connection degrees of freedoms, which improves the accuracy in identification. Several equations for the identification of joint parameters are derived utilizing FRF-DM. Joint parameters are calculated by using developed FRF decoupling relations, as well as by employing a recently developed method called Inverse Structural Modification Method (ISMM) in a case study consisting of two beams connected by a 6 × 6 stiffness and viscous damping matrices. The accuracy and the advantages of each method/formulation are discussed by using the case study based on simulated experiments.

ESTIMATION OF MODEL PARAMETERS FROM TIME SERIES BY OPCL AUTO-SYNCHRONIZATION

2004 ◽  
Vol 14 (06) ◽  
pp. 2133-2141 ◽  
Author(s):  
IOAN GROSU
Keyword(s):  
Time Series ◽  
Global Minimum ◽  
Error Function ◽  
Numerical Results ◽  
Model Parameters ◽  
Estimation Of Model Parameters ◽  
Determination Of Parameters

OPCL autosynchronization ([1997] Phys. Rev.E56, 3709–3711) is used for determination of parameters in 1-D models. Numerical results are given for noisy Duffing and logistic systems. The proposed algorithm works also for models that contain parameters nonlinearly. Numerical results show that the error function has a global minimum.

Identifiability and uncertainty analysis of the River Water Quality Model No. 1 (RWQM1)

2001 ◽  
Vol 43 (7) ◽  
pp. 329-338 ◽  
Author(s):  
P. Reichert ◽  
P. Vanrolleghem
Keyword(s):  
Water Quality ◽  
River Water ◽  
Water Quality Model ◽  
River Water Quality ◽  
Model Parameters ◽  
Water Quality Modelling ◽  
Quality Model ◽  
Model Predictions ◽  
Selection Of

State of the art models as used in activated sludge modelling and recently proposed for river water quality modelling integrate the knowledge in a certain field. If applied to data from a specific site, such models are nearly always overparameterised. This raises the question of how many parameters can be fitted in a given context and how to find identifiable parameter subsets given the experimental layout. This problem is addressed for the kinetic parameters of a simplified version of the recently published river water quality model no. 1 (RWQM1). The selection of practically identifiable parameter subsets is discussed for typical boundary conditions as a function of the measurement layout. Two methods for identifiable subset selection were applied and lead to nearly the same results. Assuming upstream and downstream measurements of dissolved substances to be available, only a few (5-8) model parameters appear to be identifiable. Extensive measurement campaigns with dedicated experiments seem to be required for successful calibration of RWQM1. The estimated prior uncertainties of the model parameters are used to estimate the uncertainty of model predictions. Finally an estimate is provided for the maximum possible decrease in prediction uncertainty achievable by a perfect determination of the values of the identifiable model parameters.

Calibrating and Validating Deterministic Traffic Models

2005 ◽  
Vol 1920 (1) ◽  
pp. 95-105 ◽  
Author(s):  
Rui Miguel Batista Paulo ◽  
Jiong Lin ◽  
Nagui M. Rouphail ◽  
Jerome Sacks
Keyword(s):  
Model Parameters ◽  
Validation Process ◽  
Highway Capacity ◽  
Traffic Models ◽  
Highway Capacity Manual ◽  
Calibration And Validation ◽  
Model Predictions ◽  
Statistical Issues ◽  
Estimation Of Model Parameters

Calibration and validation of traffic models are processes that depend on field data that are often limited but are essential for determination of inputs to the model and assessment of its reliability. Quantification and systematization of the calibration and validation process expose statistical issues inherent in the use of such data. Formalization of the calibration and validation process naturally leads to the use of Bayesian methodology for assessment of uncertainties in model predictions that arise from a multiplicity of sources, especially statistical variability in estimation and calibration of the input parameters and model discrepancy. The general problem was elucidated in an earlier paper; this paper carries out the full calibration and validation process in the context of a widely used deterministic traffic model, namely, the Highway Capacity Manual model for control delay at signalized intersection approaches. In particular, the reliability of the model was assessed through quantification of the uncertainty in the estimation of model parameters, predictions of model delay, and predictions obtained by adjusting the data used in the model. While the methods are described in a specific context, they can be used generally but are inhibited at times by computational burdens that must be overcome.

scholarly journals Multi-Index Evaluation for Flood Disaster from Sustainable Perspective: A Case Study of Xinjiang in China

2018 ◽  
Vol 15 (9) ◽  
pp. 1983 ◽  
Author(s):  
Yudan Dou ◽  
Xiaolong Xue ◽  
Zebin Zhao ◽  
Xiaowei Luo ◽  
Ankang Ji ◽  
...  
Keyword(s):  
Subjective Experience ◽  
Evaluation Model ◽  
Sustainable Construction ◽  
Model Parameters ◽  
Recognition Model ◽  
Sample Data ◽  
Index Evaluation ◽  
Fuzzy Recognition

The floods have undermined the sustainable construction of cities because of their sudden and destruction. To reduce the losses caused by floods, it is necessary to make a reasonable evaluation for historical floods and provide scientific guidance for future precaution. Previous research mainly used subjective/objective weights or barely made static analysis without considering the uncertainty and ambiguity of floods. Therefore, this study proposed a variable fuzzy recognition model, based on combined weights, to evaluate floods, including the determination of index weights and the choice of evaluation model. To make the index weights reflect both subjective experience and objective data, the combined weights were proposed and calculated based on the principle of minimum identification information. Then, the relative membership degree matrix and evaluation results can be worked out by the variable fuzzy recognition model. Conclusions indicated that the combined weights were more convincing than simply subjective or objective weights. Moreover, the variable fuzzy recognition model, by changing model parameters, got stable evaluation results of the sample data. Therefore, the model can improve the credibility of evaluation and the conclusions can provide reasonable suggestions for management departments.

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