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Статті в журналах з теми "Sobol’s indices"
Cousin, A., A. Janon, V. Maume-Deschamps, and I. Niang. "On the consistency of Sobol indices with respect to stochastic ordering of model parameters." ESAIM: Probability and Statistics 23 (2019): 387–408. http://dx.doi.org/10.1051/ps/2018001.
Повний текст джерелаWang, Zhixiang, Yongjun Lei, Dapeng Zhang, Guanri Liu, and Jie Wang. "Data-driven global sensitivity indices for the load-carrying capacity of large-diameter stiffened cylindrical shells." Advances in Mechanical Engineering 14, no. 4 (April 2022): 168781322210901. http://dx.doi.org/10.1177/16878132221090105.
Повний текст джерелаWang, Zhixiang, Yongjun Lei, Dapeng Zhang, Guanri Liu, and Jie Wang. "Data-driven global sensitivity indices for the load-carrying capacity of large-diameter stiffened cylindrical shells." Advances in Mechanical Engineering 14, no. 4 (April 2022): 168781322210901. http://dx.doi.org/10.1177/16878132221090105.
Повний текст джерелаMelillo, Nicola, and Adam S. Darwich. "A latent variable approach to account for correlated inputs in global sensitivity analysis." Journal of Pharmacokinetics and Pharmacodynamics 48, no. 5 (May 25, 2021): 671–86. http://dx.doi.org/10.1007/s10928-021-09764-x.
Повний текст джерелаSun, Xifu, Barry Croke, Stephen Roberts, and Anthony Jakeman. "Investigation of determinism-related issues in the Sobol′ low-discrepancy sequence for producing sound global sensitivity analysis indices." ANZIAM Journal 62 (December 7, 2021): C84—C97. http://dx.doi.org/10.21914/anziamj.v62.16094.
Повний текст джерелаBotshekan, Meshkat, Mazdak P. Tootkaboni, and Arghavan Louhghalam. "Global Sensitivity of Roughness-Induced Fuel Consumption to Road Surface Parameters and Car Dynamic Characteristics." Transportation Research Record: Journal of the Transportation Research Board 2673, no. 2 (February 2019): 183–93. http://dx.doi.org/10.1177/0361198118821318.
Повний текст джерелаNguyen, Trong-Ha, and Duy-Duan Nguyen. "Reliability Assessment of Steel-Concrete Composite Beams considering Metal Corrosion Effects." Advances in Civil Engineering 2020 (December 8, 2020): 1–15. http://dx.doi.org/10.1155/2020/8817809.
Повний текст джерелаMarcuccio, Gabriele, Elvio Bonisoli, Stefano Tornincasa, John E. Mottershead, Edoardo Patelli, and Weizhuo Wang. "Image decomposition and uncertainty quantification for the assessment of manufacturing tolerances in stress analysis." Journal of Strain Analysis for Engineering Design 49, no. 8 (May 27, 2014): 618–31. http://dx.doi.org/10.1177/0309324714533694.
Повний текст джерелаHariri-Ardebili, Mohammad, Golsa Mahdavi, Azam Abdollahi, and Ali Amini. "An RF-PCE Hybrid Surrogate Model for Sensitivity Analysis of Dams." Water 13, no. 3 (January 26, 2021): 302. http://dx.doi.org/10.3390/w13030302.
Повний текст джерелаNariman, Nazim Abdul. "Control efficiency optimization and Sobol’s sensitivity indices of MTMDs design parameters for buffeting and flutter vibrations in a cable stayed bridge." Frontiers of Structural and Civil Engineering 11, no. 1 (March 2017): 66–89. http://dx.doi.org/10.1007/s11709-016-0356-8.
Повний текст джерелаДисертації з теми "Sobol’s indices"
Nzang, Essono Francine. "Approche géomatique de la variabilité spatio-temporelle de la contamination microbienne des eaux récréatives." Thèse, Université de Sherbrooke, 2016. http://hdl.handle.net/11143/10211.
Повний текст джерелаAbstract : The aim of this study was to predict water faecal contamination from a bayesian probabilistic model, on a watershed scale in a farming area and on a factual scale. This project aims to better understand the influence of hydrological, environmental and temporal factors involved in the explanation of microbial contamination episodes of recreational waters. First, a bayesian probabilistic model: Weight of Evidence was developed to identify and map the probability of water levels to be contaminated by agricultural effluents, on the basis of spectrals data and geomorphologic variables. By this method, we were able to calculate weighted relationships between concentrations of Escherichia coli and distribution of key agronomic, pedologic and climatic parameters that influence the spread of these microorganisms. The results showed that the Bayesian model that was developed can be used as a prediction of microbial contamination of recreational waters. This model, with a success rate of 71%, highlighted the significant role played by the rain, which is the main cause of pollution transport. Secondly, the Bayesian probabilistic model has been the subject of a sensitivity analysis related to spatial parameters, using Sobol indications. This allowed (1) quantification of uncertainties on soil variables, land use and distance and (2) the spread of these uncertainties in the probabilistic model that is to say, the calculation of induced error in the output by the uncertainties of spatial inputs. Lastly, simulation sensitivity analysis to the various sources of uncertainty was performed to assess the contribution of each factor on the overall uncertainty taking into account their interactions. It appears that of all the scenarios, the uncertainty of the microbial contamination is directly dependent on the variability of clay soils. Sobol prime indications analysis showed that among the most likely to influence the microbial factors, the area of farmland is the first important factor in assessing the coliforms. Importance must be given on this parameter in the context of preparation for microbial contamination. Then, the second most important variable is the urban area with sensitivity shares of approximately 30%. Furthermore, estimates of the total indications are better than those of the first order, which means that the impact of parametric interaction is clearly significant for the modeling of microbial contamination. Thirdly, we propose to implement a temporal variability model of microbiological contamination on the watershed of Lake Massawippi, based on the AVSWAT model. This is a model that couples the temporal and spatial components that characterize the dynamics of coliforms. The synthesis of the main results shows that concentrations of Escherichia coli in different sub-watersheds are influenced by rain intensity. Research also concluded that best performance is obtained by multi-objective optimization. The results of these studies show the prospective of operationally providing a comprehensive understanding of the dynamics of microbial contamination of surface water.
Chastaing, Gaëlle. "Indices de Sobol généralisés pour variables dépendantes." Phd thesis, Université de Grenoble, 2013. http://tel.archives-ouvertes.fr/tel-00930229.
Повний текст джерелаChastaing, Gaëlle. "Indices de Sobol généralisés par variables dépendantes." Thesis, Grenoble, 2013. http://www.theses.fr/2013GRENM046.
Повний текст джерелаA mathematical model aims at characterizing a complex system or process that is too expensive to experiment. However, in this model, often strongly non linear, input parameters can be affected by a large uncertainty including errors of measurement of lack of information. Global sensitivity analysis is a stochastic approach whose objective is to identify and to rank the input variables that drive the uncertainty of the model output. Through this analysis, it is then possible to reduce the model dimension and the variation in the output of the model. To reach this objective, the Sobol indices are commonly used. Based on the functional ANOVA decomposition of the output, also called Hoeffding decomposition, they stand on the assumption that the incomes are independent. Our contribution is on the extension of Sobol indices for models with non independent inputs. In one hand, we propose a generalized functional decomposition, where its components is subject to specific orthogonal constraints. This decomposition leads to the definition of generalized sensitivity indices able to quantify the dependent inputs' contribution to the model variability. On the other hand, we propose two numerical methods to estimate these constructed indices. The first one is well-fitted to models with independent pairs of dependent input variables. The method is performed by solving linear system involving suitable projection operators. The second method can be applied to more general models. It relies on the recursive construction of functional systems satisfying the orthogonality properties of summands of the generalized decomposition. In parallel, we illustrate the two methods on numerical examples to test the efficiency of the techniques
Riahi, Hassen. "Analyse de structures à dimension stochastique élevée : application aux toitures bois sous sollicitation sismique." Phd thesis, Université Blaise Pascal - Clermont-Ferrand II, 2013. http://tel.archives-ouvertes.fr/tel-00881187.
Повний текст джерелаMontealegre, Scott Juan. "Initial value problem for a coupled system of Kadomtsev-Petviashvili II equations in Sobolev spaces of negative indices." Pontificia Universidad Católica del Perú, 2014. http://repositorio.pucp.edu.pe/index/handle/123456789/95255.
Повний текст джерелаTissot, Jean-Yves. "Sur la décomposition ANOVA et l'estimation des indices de Sobol'. Application à un modèle d'écosystème marin." Phd thesis, Université de Grenoble, 2012. http://tel.archives-ouvertes.fr/tel-00762800.
Повний текст джерелаTissot, Jean-yves. "Sur la décomposition ANOVA et l'estimation des indices de Sobol'. Application à un modèle d'écosystème marin." Thesis, Grenoble, 2012. http://www.theses.fr/2012GRENM064/document.
Повний текст джерелаIn the fields of modelization and numerical simulation, simulators generally depend on several input parameters whose impact on the model outputs are not always well known. The main goal of sensitivity analysis is to better understand how the model outputs are sensisitive to the parameters variations. One of the most competitive method to handle this problem when complex and potentially highly non linear models are considered is based on the ANOVA decomposition and the Sobol' indices. More specifically the latter allow to quantify the impact of each parameters on the model response. In this thesis, we are interested in the issue of the estimation of the Sobol' indices. In the first part, we revisit in a rigorous way existing methods in light of discrete harmonic analysis on cyclic groups and randomized orthogonal arrays. It allows to study theoretical properties of this method and to intriduce generalizations. In a second part, we study the Monte Carlo method for the Sobol' indices and we introduce a new approach to reduce the number of simulations of this method. In parallel with this theoretical work, we apply these methods on a marine ecosystem model
Gayrard, Emeline. "Analyse bayésienne de la gerbe d'éclats provoquée pa l'explosion d'une bombe à fragmentation naturelle." Thesis, Université Clermont Auvergne (2017-2020), 2019. http://www.theses.fr/2019CLFAC039/document.
Повний текст джерелаDuring this thesis, a method of statistical analysis on sheaf of bomb fragments, in particular on their masses, has been developed. Three samples of incomplete experimental data and a mechanical model which simulate the explosion of a ring were availables. First, a statistical model based on the mechanical model has been designed, to generate data similar to those of an experience. Then, the distribution of the masses has been studied. The classical methods of analysis being not accurate enough, a new method has been developed. It consists in representing the mass by a random variable built from a basis of chaos polynomials. This method gives good results however it doesn't allow to take into account the link between slivers. Therefore, we decided to model the masses by a stochastic process, and not a random variable. The range of fragments, which depends of the masses, has also been modeled by a process. Last, a sensibility analysis has been carried out on this range with Sobol indices. Since these indices are applied to random variables, it was necessary to adapt them to stochastic process in a way that take into account the links between the fragments. In the last part, it is shown how the results of this analysis could be improved. Specifically, the indices presented in the last part are adapted to dependent variables and therefore, they could be suitable to processes with non independent increases
Gilquin, Laurent. "Échantillonnages Monte Carlo et quasi-Monte Carlo pour l'estimation des indices de Sobol' : application à un modèle transport-urbanisme." Thesis, Université Grenoble Alpes (ComUE), 2016. http://www.theses.fr/2016GREAM042/document.
Повний текст джерелаLand Use and Transportation Integrated (LUTI) models have become a norm for representing the interactions between land use and the transportation of goods and people in a territory. These models are mainly used to evaluate alternative planning scenarios, simulating their impact on land cover and travel demand.LUTI models and other mathematical models used in various fields are most of the time based on complex computer codes. These codes often involve poorly-known inputs whose uncertainty can have significant effects on the model outputs.Global sensitivity analysis methods are useful tools to study the influence of the model inputs on its outputs. Among the large number of available approaches, the variance based method introduced by Sobol' allows to calculate sensitivity indices called Sobol' indices. These indices quantify the influence of each model input on the outputs and can detect existing interactions between inputs.In this framework, we favor a particular method based on replicated designs of experiments called replication method. This method appears to be the most suitable for our application and is advantageous as it requires a relatively small number of model evaluations to estimate first-order or second-order Sobol' indices.This thesis focuses on extensions of the replication method to face constraints arising in our application on the LUTI model Tranus, such as the presence of dependency among the model inputs, as far as multivariate outputs.Aside from that, we propose a recursive approach to sequentially estimate Sobol' indices. The recursive approach is based on the iterative construction of stratified designs, latin hypercubes and orthogonal arrays, and on the definition of a new stopping criterion. With this approach, more accurate Sobol' estimates are obtained while recycling previous sets of model evaluations. We also propose to combine such an approach with quasi-Monte Carlo sampling.An application of our contributions on the LUTI model Tranus is presented
Jannet, Basile. "Influence de la non-stationnarité du milieu de propagation sur le processus de Retournement Temporel (RT)." Thesis, Clermont-Ferrand 2, 2014. http://www.theses.fr/2014CLF22436/document.
Повний текст джерелаThe aim of this thesis is to measure and quantify the impacts of uncertainties in the Time Reversal (TR) process. These random variations, coming from diverse sources, can have a huge influence if they happen between the TR steps. On this perspective, the Stochastique Collocation (SC) method is used. Very good results in terms of effectiveness and accuracy had been noticed in previous studies in ElectroMagnetic Compatibility (EMC). The conclusions are still excellent here on TR problems. Although, when the problem dimension rises (high number of Random Variables (RV)), the SC method reaches its limits and the efficiency decreases. Therefore a study on Sensitivity Analysis (SA) techniques has been carried out. Indeed, these methods emphasize the respective influences of the random variables of a model. Among the various quantitative or qualitative SA techniques the Morris method and the Sobol total sensivity indices have been adopted. Since only a split of the inputs (point out of the predominant RV) is expected, they bring results at a lesser cost. That is why a novel method is built, combining SA techniques and the SC method. In a first step, the model is reduced with SA techniques. Then, the shortened model in which only the prevailing inputs remain, allows the SC method to show once again its efficiency with a high accuracy. This global process has been validated facing Monte Carlo results on several analytical and numerical TR cases subjet to random variations
Частини книг з теми "Sobol’s indices"
Mandel, David, and Giray Ökten. "Randomized Sobol’ Sensitivity Indices." In Springer Proceedings in Mathematics & Statistics, 395–408. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-91436-7_22.
Повний текст джерелаDwight, Richard P., Stijn G. L. Desmedt, and Pejman Shoeibi Omrani. "Sobol Indices for Dimension Adaptivity in Sparse Grids." In Simulation-Driven Modeling and Optimization, 371–95. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-27517-8_15.
Повний текст джерелаPelegrina, Guilherme Dean, Leonardo Tomazeli Duarte, Michel Grabisch, and João Marcos Travassos Romano. "An Unsupervised Capacity Identification Approach Based on Sobol’ Indices." In Modeling Decisions for Artificial Intelligence, 66–77. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-57524-3_6.
Повний текст джерелаBurnaev, Evgeny, Ivan Panin, and Bruno Sudret. "Effective Design for Sobol Indices Estimation Based on Polynomial Chaos Expansions." In Lecture Notes in Computer Science, 165–84. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-33395-3_12.
Повний текст джерелаBurnaev, Evgeny, and Ivan Panin. "Adaptive Design of Experiments for Sobol Indices Estimation Based on Quadratic Metamodel." In Statistical Learning and Data Sciences, 86–95. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-17091-6_4.
Повний текст джерелаKucherenko, Sergei, and Shugfang Song. "Derivative-Based Global Sensitivity Measures and Their Link with Sobol’ Sensitivity Indices." In Springer Proceedings in Mathematics & Statistics, 455–69. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-33507-0_23.
Повний текст джерелаDUBREUIL, Sylvain, Nathalie BARTOLI, Christian GOGU, and Thierry LEFEBVRE. "Réduction d’incertitudes en analyse multidisciplinaire basée sur une étude de sensibilité par chaos polynomial." In Ingénierie mécanique en contexte incertain, 121–50. ISTE Group, 2021. http://dx.doi.org/10.51926/iste.9010.ch4.
Повний текст джерелаCHABRIDON, Vincent, Mathieu BALESDENT, Guillaume PERRIN, Jérôme MORIO, Jean-Marc BOURINET, and Nicolas GAYTON. "Analyse de sensibilité globale ciblée pour la fiabilité en présence d’incertitudes sur les paramètres de distribution." In Ingénierie mécanique en contexte incertain, 255–304. ISTE Group, 2021. http://dx.doi.org/10.51926/iste.9010.ch7.
Повний текст джерелаBilicz, Sándor. "Sensitivity Analysis for the Inverse Problems of Electromagnetic Nondestructive Evaluation." In Studies in Applied Electromagnetics and Mechanics. IOS Press, 2020. http://dx.doi.org/10.3233/saem200032.
Повний текст джерелаKlymenko, Oleksiy V., Sergei Kucherenko, and Nilay Shah. "Constrained Global Sensitivity Analysis: Sobol’ indices for problems in non-rectangular domains." In Computer Aided Chemical Engineering, 151–56. Elsevier, 2017. http://dx.doi.org/10.1016/b978-0-444-63965-3.50027-1.
Повний текст джерелаТези доповідей конференцій з теми "Sobol’s indices"
PEREIRA, A. F. G. "Sensitivity analysis of the of the square cup stamping process using a polynomial chaos expansion." In Material Forming. Materials Research Forum LLC, 2023. http://dx.doi.org/10.21741/9781644902479-129.
Повний текст джерелаDold, Edward J., and Philip A. Voglewede. "Sensitivity Study With Sobol’ Indices in Planar Multistable Mechanisms." In ASME 2022 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2022. http://dx.doi.org/10.1115/detc2022-89414.
Повний текст джерелаBeaurepaire, Pierre, Matteo Broggi, and Edoardo Patelli. "Computation of the Sobol' Indices using Importance Sampling." In Second International Conference on Vulnerability and Risk Analysis and Management (ICVRAM) and the Sixth International Symposium on Uncertainty, Modeling, and Analysis (ISUMA). Reston, VA: American Society of Civil Engineers, 2014. http://dx.doi.org/10.1061/9780784413609.212.
Повний текст джерелаTodorov, Venelin, and Slavi Georgiev. "An Optimization Technique for Estimating Sobol Sensitivity Indices." In 17th Conference on Computer Science and Intelligence Systems. PTI, 2022. http://dx.doi.org/10.15439/2022f170.
Повний текст джерелаPetticrew, James, and Aaron Olson. "Computation of Sobol' indices using Embedded Variance Deconvolution." In Proposed for presentation at the The International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering held October 3-7, 2021 in Raleigh, NC US. US DOE, 2021. http://dx.doi.org/10.2172/1890902.
Повний текст джерелаNiewiadomski, Karol, Angel Pena-Quintal, David W. P. Thomas, and Sharmila Sumsurooah. "Sensitivity Analysis of Parasitics in Power Electronic Circuit through Sobol’ Indices." In 2021 Asia-Pacific International Symposium on Electromagnetic Compatibility (APEMC). IEEE, 2021. http://dx.doi.org/10.1109/apemc49932.2021.9597088.
Повний текст джерелаSrivastava, Ankur, Arun K. Subramaniyan, and Liping Wang. "Variance Based Global Sensitivity Analysis for Uncorrelated and Correlated Inputs With Gaussian Processes." In ASME Turbo Expo 2015: Turbine Technical Conference and Exposition. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/gt2015-43693.
Повний текст джерелаWaibel, Christoph, Georgios Mavromatidis, and Yong-Wei Zhang. "Fitness Landscape Analysis Metrics based on Sobol Indices and Fitness- and State-Distributions." In 2020 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2020. http://dx.doi.org/10.1109/cec48606.2020.9185716.
Повний текст джерелаQian, Gengjian, Michel Massenzio, and Mohamed Ichchou. "Global Sensitivity Analysis of Vehicle Restraint Systems with Screening Methods and Sobol' Indices." In the 5th International Conference. New York, New York, USA: ACM Press, 2016. http://dx.doi.org/10.1145/3036932.3036940.
Повний текст джерелаRitto, Thiago, and Edison Fabian Caballero Perez. "SENSITIVITY ANALYSIS OF THE TORSIONAL VIBRATION OF A DRILL STRING USING SOBOL INDICES." In 26th International Congress of Mechanical Engineering. ABCM, 2021. http://dx.doi.org/10.26678/abcm.cobem2021.cob2021-1603.
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