Relevant bibliographies by topics / Weighted simulation

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Weighted simulation'

Author: Grafiati
Published: 15 March 2025

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Journal articles on the topic "Weighted simulation"

1

Foshammer, Louise, Kim Guldstrand Larsen, and Anders Mariegaard. "Weighted Branching Simulation Distance for Parametric Weighted Kripke Structures." Electronic Proceedings in Theoretical Computer Science 220 (July 31, 2016): 63–75. http://dx.doi.org/10.4204/eptcs.220.6.

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Gillespie, Dan T., Min Roh, and Linda R. Petzold. "Refining the weighted stochastic simulation algorithm." Journal of Chemical Physics 130, no. 17 (May 7, 2009): 174103. http://dx.doi.org/10.1063/1.3116791.

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Gillespie, Colin S., and Andrew Golightly. "Guided proposals for efficient weighted stochastic simulation." Journal of Chemical Physics 150, no. 22 (June 14, 2019): 224103. http://dx.doi.org/10.1063/1.5090979.

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Pagès, Gilles, and Fabien Panloup. "Weighted multilevel Langevin simulation of invariant measures." Annals of Applied Probability 28, no. 6 (December 2018): 3358–417. http://dx.doi.org/10.1214/17-aap1364.

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Najarzadegan, Hossein, Mohammad Hossein Alamatsaz, Iraj Kazemi, and Debasis Kundu. "Weighted bivariate geometric distribution: Simulation and estimation." Communications in Statistics - Simulation and Computation 49, no. 9 (December 20, 2018): 2419–43. http://dx.doi.org/10.1080/03610918.2018.1520870.

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Gurevich, V. A. "Weighted minimal contrast estimates and simulation problems." Journal of Mathematical Sciences 75, no. 1 (June 1995): 1483–87. http://dx.doi.org/10.1007/bf02362563.

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Mao, B. "Molecular-dynamics investigation of molecular flexibility in ligand binding." Biochemical Journal 288, no. 1 (November 15, 1992): 109–16. http://dx.doi.org/10.1042/bj2880109.

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The molecular flexibility of an inhibitor in ligand-binding process has been investigated by the mass-weighted molecular-dynamics simulation, a computational method adopted from the standard molecular-dynamics simulation and one by which the conformational space of a biomolecular system over potential energy barriers can be sampled effectively. The bimolecular complex of the aspartyl proteinase from Rhizopus chinensis, rhizopuspepsin, and an octapeptide inhibitor was previously studied in a mass-weighted molecular-dynamics simulation; the study has been extended for investigating the molecular flexibility in ligand binding. A series of mass-weighted molecular-dynamics simulations was carried out in which libration of the inhibitor dihedral angles was parametrically controlled, and threshold values of dihedral angle libration amplitudes were observed from monitoring the sampling of the enzyme binding pocket by the inhibitor in the simulations. The computational results are consistent with the general notion of molecular-flexibility requirement for ligand binding; the freedom of dihedral rotations of side-chain groups was found to be particularly important for ligand binding. Thus the critical degree of molecular flexibility which would contribute to effective enzyme inhibition can be obtained precisely from the modified molecular-dynamics simulations; the procedure described herein represents a first step toward providing quantitative measures of such a molecular-flexibility index for inhibitor molecules that have been otherwise targeted for optimal protein-ligand interactions.
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Stankovic, Ivan, Miroslav Ciric, and Jelena Ignjatovic. "Bisimulations for weighted networks with weights in a quantale." Filomat 37, no. 11 (2023): 3335–55. https://doi.org/10.2298/fil2311335s.

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In this paper we introduce two types of simulations (forward and backward) and five types of bisimulations (forward, backward, forward-backward, backward-forward, and regular) for weighted networks with weights taken in a quntale, we describe their basic properties and provide procedures for testing the existence of a simulation or bisimulation of a given type and computing the greatest one, in cases when such simulations or bisimulations exist.We also describe basic properties of homogeneous simulations and bisimulations, which relate actors within the same weighted network, and establish relationships between heterogeneous bisimulations between two different networks and homogeneous bisimulations on these networks. In addition, we characterize the greatest forward, backward and regular bisimulations between weighted networks by means of multi-valued multimodal logics.
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Cuong, Nguyen The, and Huynh The Phung. "WEIGHTED STRUCTURAL SUPPORT VECTOR MACHINE." Journal of Computer Science and Cybernetics 37, no. 1 (March 29, 2021): 43–56. http://dx.doi.org/10.15625/1813-9663/37/1/15396.

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In binary classification problems, two classes of data seem to be different from each other. It is expected to be more complicated due to the clusters in each class also tend to be different. Traditional algorithms as Support Vector Machine (SVM) or Twin Support Vector Machine (TWSVM) cannot sufficiently exploit structural information with cluster granularity of the data, cause limitation on the capability of simulation of data trends. Structural Twin Support Vector Machine (S-TWSVM) sufficiently exploits structural information with cluster granularity for learning a represented hyperplane. Therefore, the capability of S-TWSVM’s data simulation is better than that of TWSVM. However, for the datasets where each class consists of clusters of different trends, the S-TWSVM’s data simulation capability seems restricted. Besides, the training time of S-TWSVM has not been improved compared to TWSVM. This paper proposes a new Weighted Structural - Support Vector Machine (called WS-SVM) for binary classification problems with a class-vs-clusters strategy. Experimental results show that WS-SVM could describe the tendency of the distribution of cluster information. Furthermore, both the theory and experiment show that the training time of the WS-SVM for classification problem has significantly improved compared to S-TWSVM.
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Wilson, James D., Matthew J. Denny, Shankar Bhamidi, Skyler J. Cranmer, and Bruce A. Desmarais. "Stochastic weighted graphs: Flexible model specification and simulation." Social Networks 49 (May 2017): 37–47. http://dx.doi.org/10.1016/j.socnet.2016.11.002.

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Dissertations / Theses on the topic "Weighted simulation"

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Shah, Sandeep R. "Perfect simulation of conditional and weighted models." Thesis, University of Warwick, 2004. http://wrap.warwick.ac.uk/59406/.

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This thesis is about probabilistic simulation techniques. Specifically we consider the exact or perfect sampling of spatial point process models via the dominated CFTP protocol. Fundamental among point process models is the Poisson process, which formalises the notion of complete spatial randomness; synonymous with the Poisson process is the Boolean model. The models treated here are the conditional Boolean model and the area-interaction process. The latter is obtained by weighting a Poisson process according to the area of its associated Boolean model. A fundamental tool employed in the perfect simulation of point processes are spatial birth-death processes. Perfect sampling algorithms for the conditional Boolean and area-interaction models are described. Birth-death processes are also employed in order to develop an exact omnithermal algorithm for the area-interaction process. This enables the simultaneous sampling of the process for a whole range of parameter values using a single realization. A variant of Rejection sampling, namely 2-Stage Rejection, and exact Gibbs samplers for the conditional Boolean and area-interaction processes are also developed here. A quantitative comparison of the methods employing 2-Stage Rejection, spatial birth-death processes and Gibbs samplers is carried, the performance measured by actual run times of the algorithms. Validation of the perfect simulation algorithms is carried out via x2 tests.
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Graham, Mark. "The development and application of a simulation system for diffusion-weighted MRI." Thesis, University College London (University of London), 2018. http://discovery.ucl.ac.uk/10047351/.

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Diffusion-weighted MRI (DW-MRI) is a powerful, non-invasive imaging technique that allows us to infer the structure of biological tissue. It is particularly well suited to the brain, and is used by clinicians and researchers studying its structure in health and disease. High quality data is required to accurately characterise tissue structure with DW-MRI. Obtaining such data requires the careful optimisation of the image acquisition and processing pipeline, in order to maximise image quality and minimise artefacts. This thesis extends an existing MRI simulator to create a simulation system capable of producing realistic DW-MR data, with artefacts, and applies it to improve the acquisition and processing of such data. The simulator is applied in three main ways. Firstly, a novel framework for evaluating post-processing techniques is proposed and applied to assess commonly used strategies for the correction of motion, eddy-current and susceptibility artefacts. Secondly, it is used to explore the often overlooked susceptibility-movement interaction. It is demonstrated that this adversely impacts analysis of DW-MRI data, and a simple modification to the acquisition scheme is suggested to mitigate its impact. Finally, the simulation is applied to develop a new tool to perform automatic quality control. Simulated data is used to train a classifier to detect movement artefacts in data, with performance approaching that of a classifier trained on real data whilst requiring much less manually-labelled training data. It is hoped that both the findings in this thesis and the simulation tool itself will benefit the DW-MRI community. To this end, the tool is made freely available online to aid the development and validation of methods for acquiring and processing DW-MRI data.
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Giacalone, Marco. "Lambda_c detection using a weighted Bayesian PID approach." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2016. http://amslaurea.unibo.it/11431/.

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Lo scopo della tesi è di stimare le prestazioni del rivelatore ALICE nella rivelazione del barione Lambda_c nelle collisioni PbPb usando un approccio innovativo per l'identificazione delle particelle. L'idea principale del nuovo approccio è di sostituire l'usuale selezione della particella, basata su tagli applicati ai segnali del rivelatore, con una selezione che usi le probabilità derivate dal teorema di Bayes (per questo è chiamato "pesato Bayesiano"). Per stabilire quale metodo è il più efficiente , viene presentato un confronto con altri approcci standard utilizzati in ALICE. Per fare ciò è stato implementato un software di simulazione Monte Carlo "fast", settato con le abbondanze di particelle che ci si aspetta nel nuovo regime energetico di LHC e con le prestazioni osservate del rivelatore. E' stata quindi ricavata una stima realistica della produzione di Lambda_c, combinando i risultati noti da esperimenti precedenti e ciò è stato usato per stimare la significatività secondo la statistica al RUN2 e RUN3 dell'LHC. Verranno descritti la fisica di ALICE, tra cui modello standard, cromodinamica quantistica e quark gluon plasma. Poi si passerà ad analizzare alcuni risultati sperimentali recenti (RHIC e LHC). Verrà descritto il funzionamento di ALICE e delle sue componenti e infine si passerà all'analisi dei risultati ottenuti. Questi ultimi hanno mostrato che il metodo risulta avere una efficienza superiore a quella degli usuali approcci in ALICE e che, conseguentemente, per quantificare ancora meglio le prestazioni del nuovo metodo si dovrebbe eseguire una simulazione "full", così da verificare i risultati ottenuti in uno scenario totalmente realistico.
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Potgieter, Andrew. "A Parallel Multidimensional Weighted Histogram Analysis Method." Thesis, University of Cape Town, 2014. http://pubs.cs.uct.ac.za/archive/00000986/.

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The Weighted Histogram Analysis Method (WHAM) is a technique used to calculate free energy from molecular simulation data. WHAM recombines biased distributions of samples from multiple Umbrella Sampling simulations to yield an estimate of the global unbiased distribution. The WHAM algorithm iterates two coupled, non-linear, equations, until convergence at an acceptable level of accuracy. The equations have quadratic time complexity for a single reaction coordinate. However, this increases exponentially with the number of reaction coordinates under investigation, which makes multidimensional WHAM a computationally expensive procedure. There is potential to use general purpose graphics processing units (GPGPU) to accelerate the execution of the algorithm. Here we develop and evaluate a multidimensional GPGPU WHAM implementation to investigate the potential speed-up attained over its CPU counterpart. In addition, to avoid the cost of multiple Molecular Dynamics simulations and for validation of the implementations we develop a test system to generate samples analogous to Umbrella Sampling simulations. We observe a maximum problem size dependent speed-up of approximately 19 for the GPGPU optimized WHAM implementation over our single threaded CPU optimized version. We find that the WHAM algorithm is amenable to GPU acceleration, which provides the means to study ever more complex molecular systems in reduced time periods.
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Simmler, Urs. "Simulation-News in Creo 1.0 & 2.0 & 3.0 : weighted Links : "Tipps & Tricks"." Universitätsbibliothek Chemnitz, 2013. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-qucosa-114511.

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- Rückblick Simulation-News in Creo 1.0 & Creo 2.0 - Ausblick Simulation-News in Creo 3.0 - Gewichtete Verbindungen: „Tips & Tricks“ mit konkreten Beispielen: o Lagersteifigkeiten (z.B. Wälzlager) o Mechanismus Verbindungen (Dreh-, Schub-, Zylinder, .... Gelenke) o Vorgespannte Schrauben (mit Schalen-/Balken-Elementen) o Aufbringung einer momentfreien Zwangsverschiebung o „Gesamtlast auf Punkt“: Messen der Punktverschiebung o Verbinden von Massen-Elementen o Verhindern von Singularitäten - Live-Präsentation in Creo 2.0 o Lagersteifigkeiten (z.B. Wälzlager) o Mechanismus Verbindungen (Dreh-, Schub-, Zylinder, .... Gelenke)
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Kamunge, Daniel. "A non-linear weighted least squares gas turbine diagnostic approach and multi-fuel performance simulation." Thesis, Cranfield University, 2011. http://dspace.lib.cranfield.ac.uk/handle/1826/5612.

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The gas turbine which has found numerous applications in Air, Land and Sea applications, as a propulsion system, electricity generator and prime mover, is subject to deterioration of its individual components. In the past, various methodologies have been developed to quantify this deterioration with varying degrees of success. No single method addresses all issues pertaining to gas turbine diagnostics and thus, room for improvement exists. The first part of this research investigates the feasibility of non-linear W eighted Least Squares as a gas turbine component deterioration quantification tool. Two new weighting schemes have been developed to address measurement noise. Four cases have been run to demonstrate the non-linear weighted least squares method, in conjunction with the new weighting schemes. Results demonstrate that the non-linear weighted least squares method effectively addresses measurement noise and quantifies gas path component faults with improved accuracy over its linear counterpart and over methods that do not address measurement noise. Since Gas turbine diagnostics is based on analysis of engine performance at given ambient and power setting conditions; accurate and reliable engine performance modelling and simulation models are essential for meaningful gas turbine diagnostics. The second part of this research therefore sought to develop a multi-fuel and multi-caloric simulation method with the view of improving simulation accuracy. The method developed is based on non-linear interpolation of fuel tables. Fuel tables for Jet-A, UK Natural gas, Kerosene and Diesel were produced. Six case studies were carried out and the results demonstrate that the method has significantly improved accuracy over linear interpolation based methods and methods that assume thermal perfection.
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Landon, Colin Donald. "Weighted particle variance reduction of Direct Simulation Monte Carlo for the Bhatnagar-Gross-Krook collision operator." Thesis, Massachusetts Institute of Technology, 2010. http://hdl.handle.net/1721.1/61882.

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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2010.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 67-69).
Direct Simulation Monte Carlo (DSMC)-the prevalent stochastic particle method for high-speed rarefied gas flows-simulates the Boltzmann equation using distributions of representative particles. Although very efficient in producing samples of the distribution function, the slow convergence associated with statistical sampling makes DSMC simulation of low-signal situations problematic. In this thesis, we present a control-variate-based approach to obtain a variance-reduced DSMC method that dramatically enhances statistical convergence for lowsignal problems. Here we focus on the Bhatnagar-Gross-Krook (BGK) approximation, which as we show, exhibits special stability properties. The BGK collision operator, an approximation common in a variety of fields involving particle mediated transport, drives the system towards a local equilibrium at a prescribed relaxation rate. Variance reduction is achieved by formulating desired (non-equilibrium) simulation results in terms of the difference between a non-equilibrium and a correlated equilibrium simulation. Subtracting the two simulations results in substantial variance reduction, because the two simulations are correlated. Correlation is achieved using likelihood weights which relate the relative probability of occurrence of an equilibrium particle compared to a non-equilibrium particle. The BGK collision operator lends itself naturally to the development of unbiased, stable weight evaluation rules. Our variance-reduced solutions are compared with good agreement to simple analytical solutions, and to solutions obtained using a variance-reduced BGK based particle method that does not resemble DSMC as strongly. A number of algorithmic options are explored and our final simulation method, (VR)2-BGK-DSMC, emerges as a simple and stable version of DSMC that can efficiently resolve arbitrarily low-signal flows.
by Colin Donald Landon.
S.M.
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Xu, Zhouyi. "Stochastic Modeling and Simulation of Gene Networks." Scholarly Repository, 2010. http://scholarlyrepository.miami.edu/oa_dissertations/645.

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Recent research in experimental and computational biology has revealed the necessity of using stochastic modeling and simulation to investigate the functionality and dynamics of gene networks. However, there is no sophisticated stochastic modeling techniques and efficient stochastic simulation algorithms (SSA) for analyzing and simulating gene networks. Therefore, the objective of this research is to design highly efficient and accurate SSAs, to develop stochastic models for certain real gene networks and to apply stochastic simulation to investigate such gene networks. To achieve this objective, we developed several novel efficient and accurate SSAs. We also proposed two stochastic models for the circadian system of Drosophila and simulated the dynamics of the system. The K-leap method constrains the total number of reactions in one leap to a properly chosen number thereby improving simulation accuracy. Since the exact SSA is a special case of the K-leap method when K=1, the K-leap method can naturally change from the exact SSA to an approximate leap method during simulation if necessary. The hybrid tau/K-leap and the modified K-leap methods are particularly suitable for simulating gene networks where certain reactant molecular species have a small number of molecules. Although the existing tau-leap methods can significantly speed up stochastic simulation of certain gene networks, the mean of the number of firings of each reaction channel is not equal to the true mean. Therefore, all existing tau-leap methods produce biased results, which limit simulation accuracy and speed. Our unbiased tau-leap methods remove the bias in simulation results that exist in all current leap SSAs and therefore significantly improve simulation accuracy without sacrificing speed. In order to efficiently estimate the probability of rare events in gene networks, we applied the importance sampling technique to the next reaction method (NRM) of the SSA and developed a weighted NRM (wNRM). We further developed a systematic method for selecting the values of importance sampling parameters. Applying our parameter selection method to the wSSA and the wNRM, we get an improved wSSA (iwSSA) and an improved wNRM (iwNRM), which can provide substantial improvement over the wSSA in terms of simulation efficiency and accuracy. We also develop a detailed and a reduced stochastic model for circadian rhythm in Drosophila and employ our SSA to simulate circadian oscillations. Our simulations showed that both models could produce sustained oscillations and that the oscillation is robust to noise in the sense that there is very little variability in oscillation period although there are significant random fluctuations in oscillation peeks. Moreover, although average time delays are essential to simulation of oscillation, random changes in time delays within certain range around fixed average time delay cause little variability in the oscillation period. Our simulation results also showed that both models are robust to parameter variations and that oscillation can be entrained by light/dark circles.
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Klann, Dirk. "The Role of Information Technology in the Airport Business: A Retail-Weighted Resource Management Approach for Capacity-Constrained Airports." Thesis, Cranfield University, 2009. http://hdl.handle.net/1826/4474.

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Much research has been undertaken to gain insight into business alignment of IT. This alignment basically aims to improve a firm’s performance by an improved harmonization of the business function and the IT function within a firm. The thesis discusses previous approaches and constructs an overall framework, which a potential approach needs to fit in. Being in a highly regulated industry, for airports there is little space left to increase revenues. However, the retailing business has proven to be an area that may contribute towards higher income for airport operators. Consequently, airport management should focus on supporting this business segment. Nevertheless, it needs to be taken into account that smooth airport operations are a precondition for successful retailing business at an airport. Applying the concept of information intensity, the processes of gate allocation and airport retailing have been determined to appraise the potential that may be realized upon (improved) synchronization of the two. It has been found that the lever is largest in the planning phase (i.e. prior to operations), and thus support by means of information technology (for information distribution and improved planning) may help to enable an improved overall retail performance. In order to determine potential variables, which might influence the output, a process decomposition has been conducted along with the development of an appropriate information model. The derived research model has been tested in different scenarios. For this purpose an adequate gate allocation algorithm has been developed and implemented in a purposewritten piece of software. To calibrate the model, actual data (several hundred thousand data items from Frankfurt Airport) from two flight plan seasons has been used. Key findings: The results show that under the conditions described it seems feasible to increase retail sales in the magnitude of 9% to 21%. The most influential factors (besides the constraining rule set and a retail area’s specific performance) proved to be a flight’s minimum and maximum time at a gate as well as its buffer time at gate. However, as some of the preconditions may not be accepted by airport management or national regulators, the results may be taken as an indication for cost incurred, in case the suggested approach is not considered. The transferability to other airport business models and limitations of the research approach are discussed at the end along with suggestions for future areas of research.
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Pant, Mohan Dev. "Simulating Univariate and Multivariate Burr Type III and Type XII Distributions Through the Method of L-Moments." OpenSIUC, 2011. https://opensiuc.lib.siu.edu/dissertations/401.

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The Burr families (Type III and Type XII) of distributions are traditionally used in the context of statistical modeling and for simulating non-normal distributions with moment-based parameters (e.g., Skew and Kurtosis). In educational and psychological studies, the Burr families of distributions can be used to simulate extremely asymmetrical and heavy-tailed non-normal distributions. Conventional moment-based estimators (i.e., the mean, variance, skew, and kurtosis) are traditionally used to characterize the distribution of a random variable or in the context of fitting data. However, conventional moment-based estimators can (a) be substantially biased, (b) have high variance, or (c) be influenced by outliers. In view of these concerns, a characterization of the Burr Type III and Type XII distributions through the method of L-moments is introduced. Specifically, systems of equations are derived for determining the shape parameters associated with user specified L-moment ratios (e.g., L-Skew and L-Kurtosis). A procedure is also developed for the purpose of generating non-normal Burr Type III and Type XII distributions with arbitrary L-correlation matrices. Numerical examples are provided to demonstrate that L-moment based Burr distributions are superior to their conventional moment based counterparts in the context of estimation, distribution fitting, and robustness to outliers. Monte Carlo simulation results are provided to demonstrate that L-moment-based estimators are nearly unbiased, have relatively small variance, and are robust in the presence of outliers for any sample size. Simulation results are also provided to show that the methodology used for generating correlated non-normal Burr Type III and Type XII distributions is valid and efficient. Specifically, Monte Carlo simulation results are provided to show that the empirical values of L-correlations among simulated Burr Type III (and Type XII) distributions are in close agreement with the specified L-correlation matrices.
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Books on the topic "Weighted simulation"

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Center, Langley Research, ed. Simulated dynamic response of a multi-stage compressor with variable molecular weight flow medium. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1995.

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Schwenzfeger, K. J. Comparison of ERS-1 scatterometer Monte Carlo performance simulations using a weighted nonlinear least-squares and a maximum likelihood estimation method. Neubiberg: Hochschule der Bundeswehr München, 1985.

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Micheline, Frenette, Gard Barbara, Educational Technology Center (Cambridge, Mass.), and National Institute of Education (U.S.), eds. Weight, density and matter: A study of elementary children's reasoning about density with concrete materials and computer analogs. Cambridge, MA: Educational Technology Center, Harvard Graduate School of Education, 1985.

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Bitter, Rick. LabVIEW advanced programming techniques. Boca Raton, Fla: CRC Press, 2000.

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Taqi, Mohiuddin, and Nawrocki Matt, eds. LabVIEW advanced programming techniques. Boca Raton, FL: CRC Press, 2001.

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Taqi, Mohiuddin, and Nawrocki Matt, eds. LabView advanced programming techniques. 2nd ed. Boca Raton, FL: CRC Press/Taylor & Francis Group, 2007.

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Allen, Michael P., and Dominic J. Tildesley. Advanced Monte Carlo methods. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198803195.003.0009.

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This chapter describes the ways in which the Monte Carlo importance sampling method may be adapted to improve the calculation of ensemble averages, particularly those associated with free energy differences. These approaches include umbrella sampling, non-Boltzmann sampling, the Wang–Landau method, and nested sampling. In addition, a range of special techniques have been developed to accelerate the simulation of flexible molecules, such as polymers. These approaches are illustrated with scientific examples and program code. The chapter also explains the analysis of such simulations using techniques such as weighted histograms, and acceptance ratio calculations. Practical advice on selection of methods, parameters, and the direction in which to make comparisons, are given. Monte Carlo methods for modelling phase equilibria and chemical reactions at equilibrium are described.
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Allen, Michael P., and Dominic J. Tildesley. Monte Carlo methods. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198803195.003.0004.

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The estimation of integrals by Monte Carlo sampling is introduced through a simple example. The chapter then explains importance sampling, and the use of the Metropolis and Barker forms of the transition matrix defined in terms of the underlying matrix of the Markov chain. The creation of an appropriately weighted set of states in the canonical ensemble is described in detail and the method is extended to the isothermal–isobaric, grand canonical and semi-grand ensembles. The Monte Carlo simulation of molecular fluids and fluids containing flexible molecules using a reptation algorithm is discussed. The parallel tempering or replica exchange method for more efficient exploration of the phase space is introduced, and recent advances including solute tempering and convective replica exchange algorithms are described.
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Levin, Ines, and Betsy Sinclair. Causal Inference with Complex Survey Designs. Edited by Lonna Rae Atkeson and R. Michael Alvarez. Oxford University Press, 2016. http://dx.doi.org/10.1093/oxfordhb/9780190213299.013.4.

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This article discusses methods that combine survey weighting and propensity score matching to estimate population average treatment effects. Beginning with an overview of causal inference techniques that incorporate data from complex surveys and the usefulness of survey weights, it then considers approaches for incorporating survey weights into three matching algorithms, along with their respective methodologies: nearest-neighbor matching, subclassification matching, and propensity score weighting. It also presents the results of a Monte Carlo simulation study that illustrates the benefits of incorporating survey weights into propensity score matching procedures, as well as the problems that arise when survey weights are ignored. Finally, it explores the differences between population-based inferences and sample-based inferences using real-world data from the 2012 panel of The American Panel Survey (TAPS). The article highlights the impact of social media usage on political participation, when such impact is not actually apparent in the target population.
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Simulated dynamic response of a multi-stage compressor with variable molecular weight flow medium. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1995.

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Book chapters on the topic "Weighted simulation"

1

Maletti, Andreas. "Minimizing Weighted Tree Grammars Using Simulation." In Lecture Notes in Computer Science, 56–68. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-14684-8_7.

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Alfó, Marco, Luciano Nieddu, and Cecilia Vitiello. "Cluster Weighted Beta Regression: A Simulation Study." In Statistical Learning of Complex Data, 3–11. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-21140-0_1.

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Huang, Renxiang, Huibin Jia, and Xing Huang. "A Routing Algorithm Based on Weighted Graph for Power Distribution Network." In Simulation Tools and Techniques, 104–14. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-32216-8_10.

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Sistla, Meghana, Swarat Chaudhuri, and Thomas Reps. "Symbolic Quantum Simulation with Quasimodo." In Computer Aided Verification, 213–25. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-37709-9_11.

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AbstractThe simulation of quantum circuits on classical computers is an important problem in quantum computing. Such simulation requires representations of distributions over very large sets of basis vectors, and recent work has used symbolic data-structures such as Binary Decision Diagrams (BDDs) for this purpose. In this tool paper, we present Quasimodo, an extensible, open-source Python library for symbolic simulation of quantum circuits. Quasimodo is specifically designed for easy extensibility to other backends. Quasimodo allows simulations of quantum circuits, checking properties of the outputs of quantum circuits, and debugging quantum circuits. It also allows the user to choose from among several symbolic data-structures—both unweighted and weighted BDDs, and a recent structure called Context-Free-Language Ordered Binary Decision Diagrams (CFLOBDDs)—and can be easily extended to support other symbolic data-structures.
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Pesantez-Narvaez, Jessica, and Montserrat Guillen. "Weighted Logistic Regression to Improve Predictive Performance in Insurance." In Modelling and Simulation in Management Sciences, 22–34. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-15413-4_3.

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Eichhorn, Hannah, Kerstin Hammernik, Veronika Spieker, Samira M. Epp, Daniel Rueckert, Christine Preibisch, and Julia A. Schnabel. "Physics-Aware Motion Simulation For T2*-Weighted Brain MRI." In Simulation and Synthesis in Medical Imaging, 42–52. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-44689-4_5.

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Hrdina, Jaroslav, Petr Vašík, Josef Procházka, Libor Kutěj, and Radomír Ščurek. "The Weighted Core of Games Based on Tactical Decisions." In Modelling and Simulation for Autonomous Systems, 244–52. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-43890-6_19.

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Jackson, Pamela R., Andrea Hawkins-Daarud, and Kristin R. Swanson. "Simulated Diffusion Weighted Images Based on Model-Predicted Tumor Growth." In Simulation and Synthesis in Medical Imaging, 32–40. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-59520-3_4.

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Gupta, Krishna Kumar, and Sanjay Kumar. "A Weighted Fuzzy Time Series Forecasting Method Based on Clusters and Probabilistic Fuzzy Set." In Modeling, Simulation and Optimization, 367–78. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-0836-1_28.

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Dou, Yiwen, Kuangrong Hao, and Yongsheng Ding. "Weighted Feature Correlation and Fusion Saliency." In Theory, Methodology, Tools and Applications for Modeling and Simulation of Complex Systems, 73–81. Singapore: Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-2672-0_8.

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Conference papers on the topic "Weighted simulation"

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Broadie, Mark, Yiping Du, and Ciamac C. Moallemi. "Risk estimation via weighted regression." In 2011 Winter Simulation Conference - (WSC 2011). IEEE, 2011. http://dx.doi.org/10.1109/wsc.2011.6148077.

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Shen, Jau-Ji, Chun-Hsiu Yeh, and Jinn-Ke Jan. "The Light-Weighted Coding Schemes for Images Sharing on Mobile Devices." In Modelling and Simulation. Calgary,AB,Canada: ACTAPRESS, 2013. http://dx.doi.org/10.2316/p.2013.804-032.

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"Weighted random sampling for military aircrew timetabling." In 22nd International Congress on Modelling and Simulation. Modelling and Simulation Society of Australia and New Zealand (MSSANZ), Inc., 2017. http://dx.doi.org/10.36334/modsim.2017.d3.talbot.

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Stanley, Ronald J., Nipon Theera-Umpon, Paul D. Gader, Satish Somanchi, and Dominic K. Ho. "Detecting landmines using weighted density distribution function features." In Aerospace/Defense Sensing, Simulation, and Controls, edited by Ivan Kadar. SPIE, 2001. http://dx.doi.org/10.1117/12.436943.

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Sombattheera, Chattrakul. "A light-weighted multiagent-based crowd simulation." In 2016 Second Asian Conference on Defence Technology (ACDT). IEEE, 2016. http://dx.doi.org/10.1109/acdt.2016.7437651.

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Yuan, Xiukai, and Lin Zeng. "Weighted Simulation for Failure Probability Function Estimation." 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/10.1061/9780784413609.206.

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Ji, Yibo, and Sujin Kim. "An adaptive radial basis function method using weighted improvement." In 2013 Winter Simulation Conference - (WSC 2013). IEEE, 2013. http://dx.doi.org/10.1109/wsc.2013.6721486.

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Sonntag, Sören, and Helmut Reinig. "An Efficient Weighted-Round-Robin Algorithm for Multiprocessor Architectures." In 2008 41st Annual Simulation Symposium ANSS. IEEE, 2008. http://dx.doi.org/10.1109/anss-41.2008.14.

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Fischer, Martin J., Denise M. Bevilacqua Masi, and John F. Shortle. "Simulating the performance of a Class-Based Weighted Fair Queueing system." In 2008 Winter Simulation Conference (WSC). IEEE, 2008. http://dx.doi.org/10.1109/wsc.2008.4736412.

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Ahner, Darryl. "A normalized weighted entropy measure for sensor allocation within simulations." In 2009 Winter Simulation Conference - (WSC 2009). IEEE, 2009. http://dx.doi.org/10.1109/wsc.2009.5429170.

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Reports on the topic "Weighted simulation"

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de Dieu Niyigena, Jean, Innocent Ngaruye, Joseph Nzabanita, and Martin Singull. Approximation of misclassification probabilities using quadratic classifier for repeated measurements with known covariance matrices. Linköping University Electronic Press, August 2024. http://dx.doi.org/10.3384/lith-mat-r-2024-02.

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Quadratic discriminant analysis is a well-established supervised classification method, which extends the linear the linear discriminant analysis by relaxing the assumption of equal variances across classes. In this study, quadratic discriminant analysis is used to develop a quadratic classification rule based on repeated measurements. We employ a bilinear regression model to assign new observations to predefined populations and approximate the misclassification probability. Through weighted estimators, we estimate unknown mean parameters and derive moments of the quadratic classifier. We then conduct numerical simulations to compare misclassification probabilities using true and estimated mean parameters, as well as probabilities computed through simulation. Our findings suggest that as the distance between groups widens, the misclassification probability curve decreases, indicating that classifying observations is easier in widely separated groups compared to closely clustered ones.
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Igor Manuilskiy and W.W. Lee. The Split-weight Particle Simulation Scheme for Plasmas. Office of Scientific and Technical Information (OSTI), November 1999. http://dx.doi.org/10.2172/14871.

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Schilling, O., and M. Latini. Weighted Essentially Non-Oscillatory Simulations and Modeling of Complex Hydrodynamic Flows Part 1. Regular Shock Refraction. Office of Scientific and Technical Information (OSTI), June 2004. http://dx.doi.org/10.2172/15014460.

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Latini, M., and O. Schilling. Weighted Essentially Non-Oscillatory Simulations and Modeling of Complex Hydrodynamic Flows. Part 1. Regular Shock Refraction. Office of Scientific and Technical Information (OSTI), January 2005. http://dx.doi.org/10.2172/875932.

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Patel, Reena. Complex network analysis for early detection of failure mechanisms in resilient bio-structures. Engineer Research and Development Center (U.S.), June 2021. http://dx.doi.org/10.21079/11681/41042.

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Bio-structures owe their remarkable mechanical properties to their hierarchical geometrical arrangement as well as heterogeneous material properties. This dissertation presents an integrated, interdisciplinary approach that employs computational mechanics combined with flow network analysis to gain fundamental insights into the failure mechanisms of high performance, light-weight, structured composites by examining the stress flow patterns formed in the nascent stages of loading for the rostrum of the paddlefish. The data required for the flow network analysis was generated from the finite element analysis of the rostrum. The flow network was weighted based on the parameter of interest, which is stress in the current study. The changing kinematics of the structural system was provided as input to the algorithm that computes the minimum-cut of the flow network. The proposed approach was verified using two classical problems three- and four-point bending of a simply-supported concrete beam. The current study also addresses the methodology used to prepare data in an appropriate format for a seamless transition from finite element binary database files to the abstract mathematical domain needed for the network flow analysis. A robust, platform-independent procedure was developed that efficiently handles the large datasets produced by the finite element simulations. Results from computational mechanics using Abaqus and complex network analysis are presented.
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Martin, Robert S., and Jean-Luc Cambier. Moment Preserving Adaptive Particle Weights using Octree Velocity Distributions for PIC Simulations. Fort Belvoir, VA: Defense Technical Information Center, July 2012. http://dx.doi.org/10.21236/ada593065.

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Velghe, Ineke, Bart Buffel, Veerle Vandeginste, Wim Thielemans, and Frederik Desplentere. Modelling hydrolytic, thermal, and mechanical degradation of PLA during single-screw extrusion. Universidad de los Andes, December 2024. https://doi.org/10.51573/andes.pps39.ss.dbc.1.

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Since melt processing causes degradation of poly(lactic acid) or PLA, it is crucial to understand the effect of extrusion conditions on the molecular weight reduction. Kinetic models found in literature are promising tools to describe hydrolytic, thermal, and mechanical degradation during extrusion. In order to use these models, extrusion parameters (that are equipment dependent) should be translated into the four fundamental parameters that determine degradation: moisture content in PLA, residence time, shear stress history and temperature history. This work presents a methodology to use numerical simulations to translate extrusion parameters into fundamental parameters. The results show that numerical simulations can be used successfully to describe the extrusion process based on residence time, shear stress history, and temperature history.
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Schilling, O., and M. Latini. Weighted Essentially Non-Oscillatory Simulations and Modeling of Complex Hydrodynamic Flows. Part 2. Single-Mode Richtmyer-Meshkov Instability with Reshock. Office of Scientific and Technical Information (OSTI), October 2004. http://dx.doi.org/10.2172/15014825.

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Latini, M., and O. Schilling. Weighted Essentially Non-Oscillatory Simulations and Modeling of Complex Hydrodynamic Flows. Part 2. Single-Mode Richtmyer-Meshkov Instability with Reshock. Office of Scientific and Technical Information (OSTI), April 2005. http://dx.doi.org/10.2172/15016331.

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Comola, Margherita, Rokhaya Dieye, and Bernard Fortin. Heterogeneous peer effects and gender-based interventions for teenage obesity. CIRANO, September 2022. http://dx.doi.org/10.54932/tqag9043.

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This paper explores the role of gender heterogeneity in the social diffusion of obesity among adolescents and its policy implications. We propose a generalized linear social interaction model which allows for gender-dependent heterogeneity in peer effects through the channel of social synergy. We estimate the model using data on adolescent Body Mass Index and network-based interactions. Our results show that peer effects are gender-dependent, and male students are particularly responsive to the weight of their female friends. Our simulations indicate that female-tailored interventions are likely to be more effective than a gender-neutral approach to fight obesity in schools.
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