Use of sensitivity analysis to identify influential and non-influential parameters within an aquatic ecosystem model

2012 ◽  
Vol 246 ◽  
pp. 119-130 ◽  
Author(s):  
C. Ciric ◽  
P. Ciffroy ◽  
S. Charles
Keyword(s):  
Sensitivity Analysis ◽  
Aquatic Ecosystem ◽  
Ecosystem Model ◽  
Influential Parameters

scholarly journals Global Sensitivity Analysis of a Homogenized Constrained Mixture Model of Arterial Growth and Remodeling

2021 ◽  
Author(s):  
Sebastian Brandstaeter ◽  
Sebastian L. Fuchs ◽  
Jonas Biehler ◽  
Roland C. Aydin ◽  
Wolfgang A. Wall ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Global Sensitivity Analysis ◽  
Model Parameters ◽  
Computational Studies ◽  
Growth And Remodeling ◽  
Global Sensitivity ◽  
Output Variability ◽  
Constrained Mixture ◽  
The One ◽  
Influential Parameters

AbstractGrowth and remodeling in arterial tissue have attracted considerable attention over the last decade. Mathematical models have been proposed, and computational studies with these have helped to understand the role of the different model parameters. So far it remains, however, poorly understood how much of the model output variability can be attributed to the individual input parameters and their interactions. To clarify this, we propose herein a global sensitivity analysis, based on Sobol indices, for a homogenized constrained mixture model of aortic growth and remodeling. In two representative examples, we found that 54–80% of the long term output variability resulted from only three model parameters. In our study, the two most influential parameters were the one characterizing the ability of the tissue to increase collagen production under increased stress and the one characterizing the collagen half-life time. The third most influential parameter was the one characterizing the strain-stiffening of collagen under large deformation. Our results suggest that in future computational studies it may - at least in scenarios similar to the ones studied herein - suffice to use population average values for the other parameters. Moreover, our results suggest that developing methods to measure the said three most influential parameters may be an important step towards reliable patient-specific predictions of the enlargement of abdominal aortic aneurysms in clinical practice.

scholarly journals Sensitivity Analysis for Microscopic Crowd Simulation

Algorithms ◽  
2020 ◽  
Vol 13 (7) ◽  
pp. 162
Author(s):  
Marion Gödel ◽  
Rainer Fischer ◽  
Gerta Köster
Keyword(s):  
Sensitivity Analysis ◽  
Low Cost ◽  
Input Parameter ◽  
Dimensional Subspace ◽  
Crowd Simulation ◽  
Pedestrian Dynamics ◽  
Sensitivity Indices ◽  
Expensive Problems ◽  
Influential Parameters ◽  
Typical Scenario

Microscopic crowd simulation can help to enhance the safety of pedestrians in situations that range from museum visits to music festivals. To obtain a useful prediction, the input parameters must be chosen carefully. In many cases, a lack of knowledge or limited measurement accuracy add uncertainty to the input. In addition, for meaningful parameter studies, we first need to identify the most influential parameters of our parametric computer models. The field of uncertainty quantification offers standardized and fully automatized methods that we believe to be beneficial for pedestrian dynamics. In addition, many methods come at a comparatively low cost, even for computationally expensive problems. This allows for their application to larger scenarios. We aim to identify and adapt fitting methods to microscopic crowd simulation in order to explore their potential in pedestrian dynamics. In this work, we first perform a variance-based sensitivity analysis using Sobol’ indices and then crosscheck the results by a derivative-based measure, the activity scores. We apply both methods to a typical scenario in crowd simulation, a bottleneck. Because constrictions can lead to high crowd densities and delays in evacuations, several experiments and simulation studies have been conducted for this setting. We show qualitative agreement between the results of both methods. Additionally, we identify a one-dimensional subspace in the input parameter space and discuss its impact on the simulation. Moreover, we analyze and interpret the sensitivity indices with respect to the bottleneck scenario.

scholarly journals Influential parameters for estimating the environmental impacts of geothermal power: A global sensitivity analysis study

2021 ◽  
Vol 3 ◽  
pp. 100054
Author(s):  
Andrea Paulillo ◽  
Aleksandra Kim ◽  
Christopher Mutel ◽  
Alberto Striolo ◽  
Christian Bauer ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Environmental Impacts ◽  
Global Sensitivity Analysis ◽  
Analysis Study ◽  
Global Sensitivity ◽  
Geothermal Power ◽  
Influential Parameters

Error estimation and sensitivity analysis of the 3-UPU translational parallel robot due to design parameter uncertainties

2018 ◽  
Vol 233 (8) ◽  
pp. 2713-2727 ◽  
Author(s):  
S El Hraiech ◽  
AH Chebbi ◽  
Z Affi ◽  
L Romdhane
Keyword(s):  
Sensitivity Analysis ◽  
Vertical Axis ◽  
Parallel Robot ◽  
Design Parameters ◽  
Analysis Method ◽  
Parameter Uncertainties ◽  
End Effector ◽  
Interval Analysis Method ◽  
Influential Parameters ◽  
Kinematic Errors

This work deals with the estimation and the sensitivity analysis of the 3-UPU parallel robot error. Based on the Newton–Euler formalism, the robot dynamic model is given in a closed form. This model is validated by the software ADAMS. Using the interval analysis method, a new algorithm is proposed, which estimates the errors in the motion of the end-effector and the errors in the actuator forces as a function of the design parameters uncertainties. The obtained results show that the kinematic errors are minimal at the workspace center. Moreover, these errors increase as the platform moves along the vertical axis. It is also shown that kinematic errors in the actuator joints are the most influential parameters on the manipulator accuracy. Therefore, using actuators with a higher accuracy can highly reduce the errors in motion of the platform.

Sensitivity analysis of a process-based ecosystem model: Pinpointing parameterization and structural issues

2013 ◽  
Vol 118 (2) ◽  
pp. 505-528 ◽  
Author(s):  
Christoforos Pappas ◽  
Simone Fatichi ◽  
Sebastian Leuzinger ◽  
Annett Wolf ◽  
Paolo Burlando
Keyword(s):  
Sensitivity Analysis ◽  
Ecosystem Model

scholarly journals An A*-based Bacterial Foraging Optimisation Algorithm for Global Path Planning of Unmanned Surface Vehicles

2020 ◽  
Vol 73 (6) ◽  
pp. 1247-1262
Author(s):  
Yang Long ◽  
Zheming Zuo ◽  
Yixin Su ◽  
Jie Li ◽  
Huajun Zhang
Keyword(s):  
Sensitivity Analysis ◽  
Path Planning ◽  
Optimal Parameter ◽  
A Algorithm ◽  
Unmanned Surface Vehicles ◽  
Parameter Combination ◽  
Bacterial Foraging ◽  
Optimisation Algorithm ◽  
Global Path Planning ◽  
Influential Parameters

The bacterial foraging optimisation (BFO) algorithm is a commonly adopted bio-inspired optimisation algorithm. However, BFO is not a proper choice in coping with continuous global path planning in the context of unmanned surface vehicles (USVs). In this paper, a grid partition-based BFO algorithm, named AS-BFO, is proposed to address this issue in which the enhancement is contributed by the involvement of the A* algorithm. The chemotaxis operation is redesigned in AS-BFO. Through repeated simulations, the relative optimal parameter combination of the proposed algorithm is obtained and the most influential parameters are identified by sensitivity analysis. The performance of AS-BFO is evaluated via five size grid maps and the results show that AS-BFO has advantages in USV global path planning.

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