Global Sensitivity Analysis of Cell Signalling Transduction Networks Based on Latin Hypercube Sampling Method

2007 ◽  
Author(s):  
Jianfang Jia ◽  
Hong Yue ◽  
Taiyuan Liu ◽  
Hong Wang
Keyword(s):  
Sensitivity Analysis ◽  
Sampling Method ◽  
Global Sensitivity Analysis ◽  
Cell Signalling ◽  
Latin Hypercube Sampling ◽  
Latin Hypercube ◽  
Global Sensitivity ◽  
Signalling Transduction

scholarly journals Stability and Global Sensitivity Analysis for an Agree-Disagree Model: Partial Rank Correlation Coefficient and Latin Hypercube Sampling Methods

2020 ◽  
Vol 2020 ◽  
pp. 1-14 ◽  
Author(s):  
Sara Bidah ◽  
Omar Zakary ◽  
Mostafa Rachik
Keyword(s):  
Sensitivity Analysis ◽  
Correlation Coefficient ◽  
Global Sensitivity Analysis ◽  
Equilibrium Points ◽  
Rank Correlation ◽  
Latin Hypercube Sampling ◽  
Latin Hypercube ◽  
Global Sensitivity ◽  
Existence And Stability ◽  
Partial Rank Correlation

In this paper, we present a new mathematical model that describes agree-disagree opinions during polls. We first present the model and its different compartments. Then, we use the next-generation matrix method to compute thresholds of equilibrium stability. We perform the stability analysis of equilibria to determine under which conditions these equilibrium points are stable or unstable. We show that the existence and stability of these equilibria are controlled by the calculated thresholds. Finally, we also perform several computational and statistical experiments to validate the theoretical results obtained in this work. To study the influence of various parameters on these thresholds and to identify the most influential parameters, a global sensitivity analysis is carried out based on the partial rank correlation coefficient method and the Latin hypercube sampling.

scholarly journals Stability and global sensitivity analysis of the transmission dynamics of malaria with relapse and ignorant infected humans

2022 ◽  
Author(s):  
Yves Tinda Mangongo ◽  
Joseph-Désiré Kyemba Bukweli ◽  
Justin Dupar Busili Kampempe ◽  
Rostin Matendo Mabela ◽  
Justin Manango Wazute Munganga
Keyword(s):  
Sensitivity Analysis ◽  
Recovery Rate ◽  
Global Sensitivity Analysis ◽  
Rank Correlation ◽  
Latin Hypercube Sampling ◽  
Transmission Dynamics ◽  
Asymptotically Stable ◽  
Globally Asymptotically Stable ◽  
Global Sensitivity ◽  
Partial Rank Correlation

Abstract In this paper we present a more realistic mathematical model for the transmission dynamics of malaria by extending the classical SEIRS scheme and the model of Hai-Feng Huo and Guang-Ming Qiu [21] by adding the ignorant infected humans compartment. We analyze the global asymptotically stabilities of the model by the use of the basic reproduction number R_0 and we prove that when R_0≦1, the disease-free equilibrium is globally asymptotically stable. That is malaria dies out in the population. When R_0>1, there exists a co-existing unique endemic equilibrium which is globally asymptotically stable. The global sensitivity analysis have been done through the partial rank correlation coefficient using the samples generated by the use of latin hypercube sampling method and shows that the most influence parameters in the spread of malaria are the proportion θ of infectious humans who recover and the recovery rate γ of infectious humans. In order to eradicate malaria, we have to decrease the number of ignorant infected humans by testing peoples and treat them. Numerical simulations show that malaria can be also controlled or eradicated by increasing the recovery rate γ of infectious humans, decreasing the number of ignorant infected humans and decreasing the average number n of mosquito bites.

scholarly journals GLOBAL SENSITIVITY ANALYSIS FOR TRANSFORMATION OF HOEK-BROWN FAILURE CRITERION FOR ROCK MASS

2018 ◽  
Vol 24 (5) ◽  
pp. 390-398 ◽  
Author(s):  
Jan Štefaňák ◽  
Zdeněk Kala ◽  
Lumír Miča ◽  
Arnoldas Norkus
Keyword(s):  
Sensitivity Analysis ◽  
Failure Criterion ◽  
Global Sensitivity Analysis ◽  
Latin Hypercube Sampling ◽  
Strength Criterion ◽  
Jointed Rock ◽  
Rock Massif ◽  
Order Effects ◽  
Statistical Parameters ◽  
Global Sensitivity

A variety of engineering activities require reliable evaluation of rock strength. For instance, the stability of rock slopes depends on structural geology of rock massif in which the slope is excavated. Hoek-Brown (HB) failure criterion applied in rock design practice introduces factors based on the properties of jointed rock. The non-linear finite element safety calculation is conveniently used for calculation safety the factor of slope stability. The Mohr-Coulomb (MC) failure (strength) criterion for soil is widely applied in geotechnical design. Therefore, the appropriate transformation from HB to the equivalent MC, employing angle of shearing resistance φ and cohesion c, is necessary. This article studies the effect of jointed rock massif properties on the transformed MC parameters by using Sobol’s global sensitivity analysis (SSA) and HB transformation equations. Statistical parameters needed for the evaluation of sensitivity analysis are processed using classical statistical methods upon the emulation of Latin Hypercube Sampling simulation methods. Developed and adapted by authors techniques are illustrated by processing real rock investigation data from survey of the trachyte massif located in the Czech Republic. The first and higher order effects of random inputs are identified using SSA. It is illustrated that the effects of inputs on the MC parameters varies significantly depending on the discontinuity distribution and height of the slope.

scholarly journals Parameter Identification of the 2-Chlorophenol Oxidation Model Using Improved Differential Search Algorithm

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Guang-zhou Chen ◽  
Jia-quan Wang ◽  
Ru-zhong Li
Keyword(s):  
Sensitivity Analysis ◽  
Parameter Identification ◽  
Sampling Method ◽  
Hybrid Methods ◽  
Latin Hypercube Sampling ◽  
The Other ◽  
Posteriori Probability ◽  
Initial Population ◽  
Latin Hypercube ◽  
Oxidation Model

Parameter identification plays a crucial role for simulating and using model. This paper firstly carried out the sensitivity analysis of the 2-chlorophenol oxidation model in supercritical water using the Monte Carlo method. Then, to address the nonlinearity of the model, two improved differential search (DS) algorithms were proposed to carry out the parameter identification of the model. One strategy is to adopt the Latin hypercube sampling method to replace the uniform distribution of initial population; the other is to combine DS with simplex method. The results of sensitivity analysis reveal the sensitivity and the degree of difficulty identified for every model parameter. Furthermore, the posteriori probability distribution of parameters and the collaborative relationship between any two parameters can be obtained. To verify the effectiveness of the improved algorithms, the optimization performance of improved DS in kinetic parameter estimation is studied and compared with that of the basic DS algorithm, differential evolution, artificial bee colony optimization, and quantum-behaved particle swarm optimization. And the experimental results demonstrate that the DS with the Latin hypercube sampling method does not present better performance, while the hybrid methods have the advantages of strong global search ability and local search ability and are more effective than the other algorithms.

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