Relevant bibliographies by topics / Varianty montáže

Contents

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

Academic literature on the topic 'Varianty montáže'

Author: Grafiati
Published: 4 June 2021
Last updated: 5 February 2022

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Journal articles on the topic "Varianty montáže"

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Felix, C. "Logistische Modellierung von Montagesystemen*/Logistic-based modeling of assembly systems." wt Werkstattstechnik online 108, no. 04 (2018): 263–66. http://dx.doi.org/10.37544/1436-4980-2018-04-69.

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Die wirtschaftliche Bedeutung der Montage steigt durch die fortschreitende Kundenorientierung stetig an. Individuelle Kundenwünsche führen zu einem Anstieg der Produktvarianten. Die Variantenbildung findet meist im letzten Produktionsschritt statt – in Form der Montage. Um den Montagevorgang bestmöglich auszuführen, stehen verschiedenste Organisationsformen zur Auswahl. Dieser Beitrag beschreibt logistikrelevante Differenzierungskriterien zur Charakterisierung von Montagesystemtypen.   The economic importance of assembly is steadily increasing due to the ongoing customer orientation. Individual customer requests lead to an increase in product variants. The variant formation usually takes place in the last production step – in the form of assembly. In order to carry out the assembly process in the best possible way, a variety of organizational forms is available. This article describes in terms of logistics relevant criteria for the characterization of assembly systems.
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Morrow, Jarrett D., and Brandon W. Higgs. "CallSim: Evaluation of Base Calls Using Sequencing Simulation." ISRN Bioinformatics 2012 (December 12, 2012): 1–10. http://dx.doi.org/10.5402/2012/371718.

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Accurate base calls generated from sequencing data are required for downstream biological interpretation, particularly in the case of rare variants. CallSim is a software application that provides evidence for the validity of base calls believed to be sequencing errors and it is applicable to Ion Torrent and 454 data. The algorithm processes a single read using a Monte Carlo approach to sequencing simulation, not dependent upon information from any other read in the data set. Three examples from general read correction, as well as from error-or-variant classification, demonstrate its effectiveness for a robust low-volume read processing base corrector. Specifically, correction of errors in Ion Torrent reads from a study involving mutations in multidrug resistant Staphylococcus aureus illustrates an ability to classify an erroneous homopolymer call. In addition, support for a rare variant in 454 data for a mixed viral population demonstrates “base rescue” capabilities. CallSim provides evidence regarding the validity of base calls in sequences produced by 454 or Ion Torrent systems and is intended for hands-on downstream processing analysis. These downstream efforts, although time consuming, are necessary steps for accurate identification of rare variants.
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Schmid, Martin, Neil Burch, Marc Lanctot, Matej Moravcik, Rudolf Kadlec, and Michael Bowling. "Variance Reduction in Monte Carlo Counterfactual Regret Minimization (VR-MCCFR) for Extensive Form Games Using Baselines." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 2157–64. http://dx.doi.org/10.1609/aaai.v33i01.33012157.

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Learning strategies for imperfect information games from samples of interaction is a challenging problem. A common method for this setting, Monte Carlo Counterfactual Regret Minimization (MCCFR), can have slow long-term convergence rates due to high variance. In this paper, we introduce a variance reduction technique (VR-MCCFR) that applies to any sampling variant of MCCFR. Using this technique, periteration estimated values and updates are reformulated as a function of sampled values and state-action baselines, similar to their use in policy gradient reinforcement learning. The new formulation allows estimates to be bootstrapped from other estimates within the same episode, propagating the benefits of baselines along the sampled trajectory; the estimates remain unbiased even when bootstrapping from other estimates. Finally, we show that given a perfect baseline, the variance of the value estimates can be reduced to zero. Experimental evaluation shows that VR-MCCFR brings an order of magnitude speedup, while the empirical variance decreases by three orders of magnitude. The decreased variance allows for the first time CFR+ to be used with sampling, increasing the speedup to two orders of magnitude.
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Frampton, Matthew, Elena R. Schiff, Nikolas Pontikos, Anthony W. Segal, and Adam P. Levine. "Seqfam: A python package for analysis of Next Generation Sequencing DNA data in families." F1000Research 7 (March 6, 2018): 281. http://dx.doi.org/10.12688/f1000research.13930.1.

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This article introduces seqfam, a python package which is primarily designed for analysing next generation sequencing (NGS) DNA data from families with known pedigree information in order to identify rare variants that are potentially causal of a disease/trait of interest. It uses the popular and versatile Pandas library, and can be straightforwardly integrated into existing analysis code/pipelines. Seqfam can be used to verify pedigree information, to perform Monte Carlo gene dropping, to undertake regression-based gene burden testing, and to identify variants which segregate by affection status in families via user-defined pattern of occurrence rules. Additionally, it can generate scripts for running analyses in a “MapReduce pattern” on a computer cluster, something which is usually desirable in NGS data analysis and indeed “big data” analysis in general. This article summarises how seqfam’s main user functions work and motivates their use. It also provides explanatory context for example scripts and data included in the package which demonstrate use cases. With respect to verifying pedigree information, software exists for efficiently calculating kinship coefficients, so seqfam performs the necessary extra steps of mapping pedigrees and kinship coefficients to expected and observed degrees of relationship respectively. Gene dropping and the application of variant pattern of occurrence rules in families can provide evidence for a variant being causal. The authors are unaware of other software which performs these tasks in familial cohorts, so seqfam fulfils this need. Gene burden rather than single marker tests are often used to detect rare causal variants due to greater power. Seqfam may be an attractive alternative to existing gene burden testing software due to its flexibility, particularly in grouping and aggregating variants.
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PORTER, K. A., C. L. BURCH, C. POOLE, J. J. JULIANO, S. R. COLE, and S. R. MESHNICK. "Uncertain outcomes: adjusting for misclassification in antimalarial efficacy studies." Epidemiology and Infection 139, no. 4 (July 12, 2010): 544–51. http://dx.doi.org/10.1017/s0950268810001652.

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SUMMARYEvaluation of antimalarial efficacy is difficult because recurrent parasitaemia can be due to recrudescence or re-infection. PCR is used to differentiate between recrudescences and re-infections by comparing parasite allelic variants before and after treatment. However, PCR-corrected results are susceptible to misclassification: false positives, due to re-infection by the same variant present in the patient before treatment; and false negatives, due to variants that are present but too infrequent to be detected in the pre-treatment PCR, but are then detectable post-treatment. This paper aimed to explore factors affecting the probability of false positives and proposes a Monte Carlo uncertainty analysis to account for both types of misclassification. Higher levels of transmission intensity, increased multiplicity of infection, and limited allelic variation resulted in more false recrudescences. The uncertainty analysis exploits characteristics of study data to minimize bias in the estimate of efficacy and can be applied to areas of different transmission intensity.
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Ontañón, Santiago. "Combinatorial Multi-armed Bandits for Real-Time Strategy Games." Journal of Artificial Intelligence Research 58 (March 29, 2017): 665–702. http://dx.doi.org/10.1613/jair.5398.

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Games with large branching factors pose a significant challenge for game tree search algorithms. In this paper, we address this problem with a sampling strategy for Monte Carlo Tree Search (MCTS) algorithms called "naive sampling", based on a variant of the Multi-armed Bandit problem called "Combinatorial Multi-armed Bandits" (CMAB). We analyze the theoretical properties of several variants of naive sampling, and empirically compare it against the other existing strategies in the literature for CMABs. We then evaluate these strategies in the context of real-time strategy (RTS) games, a genre of computer games characterized by their very large branching factors. Our results show that as the branching factor grows, naive sampling outperforms the other sampling strategies.
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Belomestny, D. V., L. S. Iosipoi, and N. K. Zhivotovskiy. "Variance Reduction in Monte Carlo Estimators via Empirical Variance Minimization." Doklady Mathematics 98, no. 2 (September 2018): 494–97. http://dx.doi.org/10.1134/s1064562418060261.

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de los Campos, Gustavo, Torsten Pook, Agustin Gonzalez-Reymundez, Henner Simianer, George Mias, and Ana I. Vazquez. "ANOVA-HD: Analysis of variance when both input and output layers are high-dimensional." PLOS ONE 15, no. 12 (December 14, 2020): e0243251. http://dx.doi.org/10.1371/journal.pone.0243251.

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Modern genomic data sets often involve multiple data-layers (e.g., DNA-sequence, gene expression), each of which itself can be high-dimensional. The biological processes underlying these data-layers can lead to intricate multivariate association patterns. We propose and evaluate two methods to determine the proportion of variance of an output data set that can be explained by an input data set when both data panels are high dimensional. Our approach uses random-effects models to estimate the proportion of variance of vectors in the linear span of the output set that can be explained by regression on the input set. We consider a method based on an orthogonal basis (Eigen-ANOVA) and one that uses random vectors (Monte Carlo ANOVA, MC-ANOVA) in the linear span of the output set. Using simulations, we show that the MC-ANOVA method gave nearly unbiased estimates. Estimates produced by Eigen-ANOVA were also nearly unbiased, except when the shared variance was very high (e.g., >0.9). We demonstrate the potential insight that can be obtained from the use of MC-ANOVA and Eigen-ANOVA by applying these two methods to the study of multi-locus linkage disequilibrium in chicken (Gallus gallus) genomes and to the assessment of inter-dependencies between gene expression, methylation, and copy-number-variants in data from breast cancer tumors from humans (Homo sapiens). Our analyses reveal that in chicken breeding populations ~50,000 evenly-spaced SNPs are enough to fully capture the span of whole-genome-sequencing genomes. In the study of multi-omic breast cancer data, we found that the span of copy-number-variants can be fully explained using either methylation or gene expression data and that roughly 74% of the variance in gene expression can be predicted from methylation data.
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Belomestny, D., L. Iosipoi, and N. Zhivotovskiy. "Variance Reduction for Monte Carlo Methods." Доклады академии наук 482, no. 6 (October 2018): 627–30. http://dx.doi.org/10.31857/s086956520002903-6.

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Pilleboue, Adrien, Gurprit Singh, David Coeurjolly, Michael Kazhdan, and Victor Ostromoukhov. "Variance analysis for Monte Carlo integration." ACM Transactions on Graphics 34, no. 4 (July 27, 2015): 1–14. http://dx.doi.org/10.1145/2766930.

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Dissertations / Theses on the topic "Varianty montáže"

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Juřicová, Vendula. "Koncept montážní linky pro montáž centrální části systému termoregulace motoru." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2015. http://www.nusl.cz/ntk/nusl-232183.

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This diploma thesis is focused on design of assemble unit technology for mounting the central part of motor heat regulation system. In the beginning the current status is described,  followed by the analysis of mounting options, specifying assembly times and determining cycles of the assebly line and developing logistic support. The resulting layout should be ergonomically acceptable, cost-effective and efficient.
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Jůzl, Martin. "Výrobní hala LD Seating - stavebně technologický projekt." Master's thesis, Vysoké učení technické v Brně. Fakulta stavební, 2018. http://www.nusl.cz/ntk/nusl-371963.

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The aim of the diploma thesis is a building-technological project on the production and assembly hall LD Seating in Boskovice u Brna. The solution is influenced by the existing hall in the area of the investor, where there will be a future new building. Based on this fact, the appropriate measures are chosen. The project puts emphasis on the off-road transport and the technological process of assembly of the prefabricated reinforced concrete hall, which will be solved from the financial and time point of view. The workflow will be affected by machine assembly, site facilities, and wider transport relationships. The project also solves the concept of the whole issue as a whole. All building objects are taken into account. Based on this, an object schedule and budget are developed.
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Kánová, Eliška. "Zhodnocení běžných účtů metodami operačního výzkumu." Master's thesis, Vysoká škola ekonomická v Praze, 2013. http://www.nusl.cz/ntk/nusl-194229.

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The aim of this diploma thesis is a selection of the best current account. This thesis describes how the bank system functions in the Czech Republic. The characteristics of the banking institutions which provide current accounts and the characteristics of the compared current accounts are presented in this thesis. The Monte Carlo method and the methods multi-criteria assessment of variants are described theoretically. The selection is based on the methods of the operational research. The first part of the practical chapter focuses on the Monte Carlo method which selects the best account by charges for different types of clients. The methods of multi-criteria assessment of variants, specifically methods TOPSIS and PROMETHEE, are also applied. The calculations are carried out by add-in SANNA for MS Excel. In conclusion, both approaches to solution are compared and the current account according to the preferences of each client type is recommended.
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Wilhelm, Pavel. "Návrh variant racionalizace operace vkládání skel v montážní lince Škoda Auto." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2014. http://www.nusl.cz/ntk/nusl-231414.

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This thesis focuses on the windscreen mounting options on the assembly line at Škoda Auto in Mladá Boleslav. The aim is to describe the possible assembly options and to determine the optimal variant. In the first part the key theoretical information is described, followed by an analysis of the current state. After the introduction of two new proposals the variatiants are compared to each other in terms of finance and overall suitability using multicriteria method.
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Rowland, Kelly L. "Advanced Quadrature Selection for Monte Carlo Variance Reduction." Thesis, University of California, Berkeley, 2018. http://pqdtopen.proquest.com/#viewpdf?dispub=10817512.

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Neutral particle radiation transport simulations are critical for radiation shielding and deep penetration applications. Arriving at a solution for a given response of interest can be computationally difficult because of the magnitude of particle attenuation often seen in these shielding problems. Hybrid methods, which aim to synergize the individual favorable aspects of deterministic and stochastic solution methods for solving the steady-state neutron transport equation, are commonly used in radiation shielding applications to achieve statistically meaningful results in a reduced amount of computational time and effort. The current state of the art in hybrid calculations is the Consistent Adjoint-Driven Importance Sampling (CADIS) and Forward-Weighted CADIS (FW-CADIS) methods, which generate Monte Carlo variance reduction parameters based on deterministically-calculated scalar flux solutions. For certain types of radiation shielding problems, however, results produced using these methods suffer from unphysical oscillations in scalar flux solutions that are a product of angular discretization. These aberrations are termed “ray effects”.

The Lagrange Discrete Ordinates (LDO) equations retain the formal structure of the traditional discrete ordinates formulation of the neutron transport equation and mitigate ray effects at high angular resolution. In this work, the LDO equations have been implemented in the Exnihilo parallel neutral particle radiation transport framework, with the deterministic scalar flux solutions passed to the Automated Variance Reduction Generator (ADVANTG) software and the resultant Monte Carlo variance reduction parameters’ efficacy assessed based on results from MCNP5. Studies were conducted in both the CADIS and FW-CADIS contexts, with the LDO equations’ variance reduction parameters seeing their best performance in the FW-CADIS method, especially for photon transport.

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Kozelský, Aleš. "Realizace montážní linky ventilů AdBlue." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2011. http://www.nusl.cz/ntk/nusl-229424.

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This diploma thesis concerns in design and realization of assembling line of a 2/2 seat valve for commercial vehicles sector. Design is using Autodesk Inventor. Thesis describes phases and goals of project management – in this case management of technological/manufacturing transfer.
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Aghedo, Maurice Enoghayinagbon. "Variance reduction in Monte Carlo methods of estimating distribution functions." Thesis, Imperial College London, 1985. http://hdl.handle.net/10044/1/37385.

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Péraud, Jean-Philippe M. (Jean-Philippe Michel). "Low variance methods for Monte Carlo simulation of phonon transport." Thesis, Massachusetts Institute of Technology, 2011. http://hdl.handle.net/1721.1/69799.

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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Materials Science and Engineering, 2011.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 95-97).
Computational studies in kinetic transport are of great use in micro and nanotechnologies. In this work, we focus on Monte Carlo methods for phonon transport, intended for studies in microscale heat transfer. After reviewing the theory of phonons, we use scientific literature to write a Monte Carlo code solving the Boltzmann Transport Equation for phonons. As a first improvement to the particle method presented, we choose to use the Boltzmann Equation in terms of energy as a more convenient and accurate formulation to develop such a code. Then, we use the concept of control variates in order to introduce the notion of deviational particles. Noticing that a thermalized system at equilibrium is inherently a solution of the Boltzmann Transport Equation, we take advantage of this deterministic piece of information: we only simulate the deviation from a nearby equilibrium, which removes a great part of the statistical uncertainty. Doing so, the standard deviation of the result that we obtain is proportional to the deviation from equilibrium. In other words, we are able to simulate signals of arbitrarily low amplitude with no additional computational cost. After exploring two other variants based on the idea of control variates, we validate our code on a few theoretical results derived from the Boltzmann equation. Finally, we present a few applications of the methods.
by Jean-Philippe M. Péraud.
S.M.
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Whittle, Joss. "Quality assessment and variance reduction in Monte Carlo rendering algorithms." Thesis, Swansea University, 2018. https://cronfa.swan.ac.uk/Record/cronfa40271.

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Over the past few decades much work has been focused on the area of physically based rendering which attempts to produce images that are indistinguishable from natural images such as photographs. Physically based rendering algorithms simulate the complex interactions of light with physically based material, light source, and camera models by structuring it as complex high dimensional integrals [Kaj86] which do not have a closed form solution. Stochastic processes such as Monte Carlo methods can be structured to approximate the expectation of these integrals, producing algorithms which converge to the true rendering solution as the amount of computation is increased in the limit. When a finite amount of computation is used to approximate the rendering solution, images will contain undesirable distortions in the form of noise from under-sampling in image regions with complex light interactions. An important aspect of developing algorithms in this domain is to have a means of accurately comparing and contrasting the relative performance gains between different approaches. Image Quality Assessment (IQA) measures provide a way of condensing the high dimensionality of image data to a single scalar value which can be used as a representative measure of image quality and fidelity. These measures are largely developed in the context of image datasets containing natural images (photographs) coupled with their synthetically distorted versions, and quality assessment scores given by human observers under controlled viewing conditions. Inference using these measures therefore relies on whether the synthetic distortions used to develop the IQA measures are representative of the natural distortions that will be seen in images from domain being assessed. When we consider images generated through stochastic rendering processes, the structure of visible distortions that are present in un-converged images is highly complex and spatially varying based on lighting and scene composition. In this domain the simple synthetic distortions used commonly to train and evaluate IQA measures are not representative of the complex natural distortions from the rendering process. This raises a question of how robust IQA measures are when applied to physically based rendered images. In this thesis we summarize the classical and recent works in the area of physicallybased rendering using stochastic approaches such as Monte Carlo methods. We develop a modern C++ framework wrapping MPI for managing and running code on large scale distributed computing environments. With this framework we use high performance computing to generate a dataset of Monte Carlo images. From this we provide a study on the effectiveness of modern and classical IQA measures and their robustness when evaluating images generated through stochastic rendering processes. Finally, we build on the strengths of these IQA measures and apply modern deep-learning methods to the No Reference IQA problem, where we wish to assess the quality of a rendered image without knowing its true value.
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Frendin, Carl, and Andreas Sjöroos. "Go Go! - Evaluating Different Variants of Monte Carlo Tree Search for Playing Go." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-157520.

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Monte Carlo Tree Search (MCTS) is a Go algorithm that is used in many recent strong go playing agents. In this report we test and compare different algorithms related to Monte Carlo simulation, seeing how well they do against each other under different time constraints on consumer hardware. This is done with our own implementation of Go rules and algorithms written in Java. The All Moves As First (AMAF) algorithmhad the best performance in the performed tests.
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Books on the topic "Varianty montáže"

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Zhao, Zhong. Sensitivity of propensity score methods to the specifications. Bonn, Germany: IZA, 2005.

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Steen, O. A. Guide to wetland ecosystems of the very dry montane interior Douglas-fir subzone eastern Fraser Plateau variant (IDFb2) in the Cariboo Forest Region, British Columbia. Victoria, B.C: BC Ministry of Forests and Lands, 1988.

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Richardson, Matthew. Drawing inferences from statistics based on multi-year asset returns. Cambridge, MA: National Bureau of Economic Research, 1990.

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Cook, Monte. Monte Cooks Arcana Evolved: A Variant Player's Handbook (Sword and Sorcery). Sword & Sorcery Studio, 2005.

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Boudreau, Joseph F., and Eric S. Swanson. Monte Carlo methods. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198708636.003.0007.

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Monte Carlo methods are those designed to obtain numerical answers with the use of random numbers . This chapter discusses random engines, which provide a pseudo-random pattern of bits, and their use in for sampling a variety of nonuniform distributions, for both continuous and discrete variables. A wide selection of uniform and nonuniform variate generators from the C++ standard library are reviewed, and common techniques for generating custom nonuniform variates are discussed. The chapter presents the uses of Monte Carlo to evaluate integrals, particularly multidimensional integrals, and then introduces the important method of Markov chain Monte Carlo, suitable for solving a wide range of scientific problems that require the sampling of complicated multivariate distributions. Relevant topics in probability and statistics are also introduced in this chapter. Finally, the topics of thermalization, autocorrelation, multimodality, and Gibbs sampling are presented.
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Succi, Sauro. Numerical Methods for the Kinetic Theory of Fluids. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780199592357.003.0010.

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This chapter provides a bird’s eye view of the main numerical particle methods used in the kinetic theory of fluids, the main purpose being of locating Lattice Boltzmann in the broader context of computational kinetic theory. The leading numerical methods for dense and rarified fluids are Molecular Dynamics (MD) and Direct Simulation Monte Carlo (DSMC), respectively. These methods date of the mid 50s and 60s, respectively, and, ever since, they have undergone a series of impressive developments and refinements which have turned them in major tools of investigation, discovery and design. However, they are both very demanding on computational grounds, which motivates a ceaseless demand for new and improved variants aimed at enhancing their computational efficiency without losing physical fidelity and vice versa, enhance their physical fidelity without compromising computational viability.
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An empirical comparison of univariate and multivariate repeated measures analysis techniques when applied to motor performance data: A Monte Carlo study. 1991.

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An empirical comparison of univariate and multivariate repeated measures analysis techniques when applied to motor performance data: A Monte Carlo study. 1989.

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Sensitivity Analysis: Gauging the Worth of Scientific Models. Chichester, UK: John WIley & Sons, Ltd., 2000.

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Book chapters on the topic "Varianty montáže"

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Barbu, Adrian, and Song-Chun Zhu. "Metropolis Methods and Variants." In Monte Carlo Methods, 71–96. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-13-2971-5_4.

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Barbu, Adrian, and Song-Chun Zhu. "Gibbs Sampler and Its Variants." In Monte Carlo Methods, 97–121. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-13-2971-5_5.

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Dupree, Stephen A., and Stanley K. Fraley. "Variance Reduction Techniques." In A Monte Carlo Primer, 139–74. Boston, MA: Springer US, 2002. http://dx.doi.org/10.1007/978-1-4419-8491-3_6.

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Dupree, Stephen A., and Stanley K. Fraley. "Variance Reduction Techniques." In A Monte Carlo Primer, 75–108. Boston, MA: Springer US, 2004. http://dx.doi.org/10.1007/978-1-4419-9036-5_6.

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Hillier, Frederick S., and Bennett L. Fox. "Analysis Of Variance." In Strategies for Quasi-Monte Carlo, 183–208. Boston, MA: Springer US, 1999. http://dx.doi.org/10.1007/978-1-4615-5221-5_9.

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Hillier, Frederick S., and Bennett L. Fox. "Smoothing Variate Generation." In Strategies for Quasi-Monte Carlo, 177–82. Boston, MA: Springer US, 1999. http://dx.doi.org/10.1007/978-1-4615-5221-5_8.

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Robert, Christian P., and George Casella. "Controling Monte Carlo Variance." In Springer Texts in Statistics, 123–56. New York, NY: Springer New York, 2004. http://dx.doi.org/10.1007/978-1-4757-4145-2_4.

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Leydold, Josef, Erich Janka, and Wolfgang Hörmann. "Variants of Transformed Density Rejection and Correlation Induction." In Monte Carlo and Quasi-Monte Carlo Methods 2000, 345–56. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/978-3-642-56046-0_23.

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Asmussen, Søren, and Asger Hobolth. "Markov Bridges, Bisection and Variance Reduction." In Monte Carlo and Quasi-Monte Carlo Methods 2010, 3–22. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-27440-4_1.

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Manly, Bryan F. J. "Analysis of variance." In Randomization and Monte Carlo Methods in Biology, 64–90. Boston, MA: Springer US, 1991. http://dx.doi.org/10.1007/978-1-4899-2995-2_5.

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Conference papers on the topic "Varianty montáže"

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Ma, Junmei, and Chenglong Xu. "Modeling of Variance Swap and Improved Control Variate for Monte Carlo Method." In 2009 International Conference on Business Intelligence and Financial Engineering (BIFE). IEEE, 2009. http://dx.doi.org/10.1109/bife.2009.170.

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McGuinness, Cameron. "Classification of Monte Carlo tree search variants." In 2016 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2016. http://dx.doi.org/10.1109/cec.2016.7743816.

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Tan, Changbai, Theodor Freiheit, Kira Barton, Mihaela Banu, and S. Jack Hu. "Robustness Optimization of Product Assembly Architecture for Personalization." In ASME 2020 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/imece2020-23654.

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Abstract Personalization has received extensive attention as a new manufacturing paradigm to address increased market demand for personalized products. An open product architecture that assembling common, customized, and personalized modules is regarded as a key enabler for product personalization, which can deliver one-of-a-kind products for individual customers at near mass production efficiency. Offering the best product architecture should consider the variations in design variables and parameters that influence the performance of a product architecture. This is especially true when designing open architecture for personalized products as many uncertain design quantities need to be considered in early product design stage. A robustness optimization method is proposed to simultaneously optimize product variety, module variant selection, and configuration of personalized module variants for a personalized assembly architecture. First, a profit model is developed to measure the performance of a product architecture, which incorporates individual customer preferences and manufacturing cost. A three-step process is proposed to model heterogeneous customer preferences: conjoint analysis of the preferences of a sample of customers from target market, market segmentation by a multi-variate normal mixture method, and simulation of personal preferences for a broader market by Monte-Carlo simulation. Thus, the simulated individual customer preferences are used to predict the sales and profit of product offerings. Second, the variation of profit associated with a product family architecture due to the uncertainty in customer preference and manufacturing cost estimates is formulated by a sensitivity analysis. A robustness index is defined by combining the objectives of maximizing profit and minimizing its variation. Lastly, a robustness optimization model is established to optimize product architecture by maximizing its robustness index. The proposed method is demonstrated with a personalized bicycle architecture design example.
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Tak, Mandy J. W., Marc Lanctot, and Mark H. M. Winands. "Monte Carlo Tree Search variants for simultaneous move games." In 2014 IEEE Conference on Computational Intelligence and Games (CIG). IEEE, 2014. http://dx.doi.org/10.1109/cig.2014.6932889.

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Florentin, Olariu Emanuel. "Monte Carlo Variance Reduction. Importance Sampling Techniques." In 2009 11th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC). IEEE, 2009. http://dx.doi.org/10.1109/synasc.2009.56.

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Greve, Erik, Christoph Rennpferdt, Tobias Hartwich, and Dieter Krause. "Determination of Future Robust Product Features for Modular Product Family Design." In ASME 2019 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/imece2019-10497.

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Abstract Modular product architecture design allows product variants to be derived with little effort and cost. An essential part of designing modular product architectures is fulfilling customer-relevant product features, which represent the differentiating aspects for the customer and, thus, stand for the economic success of a product variant. However, product features are not only subject to high fluctuations due to changing environmental influences, but are also of varying relevance to customers over time. Not considering these aspects in the development phase can lead to costly changes in the product architecture later on. To counteract this, these two perspectives are merged and a methodical approach is introduced that identifies new product features and analyses their future development in the context of customer benefit. For this purpose, the current and future relevance to customers as well as uncertainties are calculated using Adaptive Conjoint Analysis and a Monte Carlo simulation. The results are consolidated in a visualization and the product features are classified according to their future implementation in robust product architecture. The procedure is explained using the example of a product family of vacuum cleaning robots.
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Bixler, Joel N., Brett H. Hokr, Aidan Winblad, Gabriel Elpers, Byron Zollars, and Robert J. Thomas. "Methods for variance reduction in Monte Carlo simulations." In SPIE BiOS, edited by E. Duco Jansen. SPIE, 2016. http://dx.doi.org/10.1117/12.2213470.

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Zhang, Pushi, Li Zhao, Guoqing Liu, Jiang Bian, Minlie Huang, Tao Qin, and Tie-Yan Liu. "Independence-aware Advantage Estimation." In Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. California: International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/461.

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Most of existing advantage function estimation methods in reinforcement learning suffer from the problem of high variance, which scales unfavorably with the time horizon. To address this challenge, we propose to identify the independence property between current action and future states in environments, which can be further leveraged to effectively reduce the variance of the advantage estimation. In particular, the recognized independence property can be naturally utilized to construct a novel importance sampling advantage estimator with close-to-zero variance even when the Monte-Carlo return signal yields a large variance. To further remove the risk of the high variance introduced by the new estimator, we combine it with existing Monte-Carlo estimator via a reward decomposition model learned by minimizing the estimation variance. Experiments demonstrate that our method achieves higher sample efficiency compared with existing advantage estimation methods in complex environments.
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Li, Ximing, Changchun Li, Jinjin Chi, and Jihong Ouyang. "Variance Reduction in Black-box Variational Inference by Adaptive Importance Sampling." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. California: International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/333.

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Overdispersed black-box variational inference employs importance sampling to reduce the variance of the Monte Carlo gradient in black-box variational inference. A simple overdispersed proposal distribution is used. This paper aims to investigate how to adaptively obtain better proposal distribution for lower variance. To this end, we directly approximate the optimal proposal in theory using a Monte Carlo moment matching step at each variational iteration. We call this adaptive proposal moment matching proposal (MMP). Experimental results on two Bayesian models show that the MMP can effectively reduce variance in black-box learning, and perform better than baseline inference algorithms.
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Beretta, Gian Paolo, and Nicolas G. Hadjiconstantinou. "Steepest Entropy Ascent Models of the Boltzmann Equation: Comparisons With Hard-Sphere Dynamics and Relaxation-Time Models for Homogeneous Relaxation From Highly Non-Equilibrium States." In ASME 2013 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/imece2013-64905.

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We present a family of steepest entropy ascent (SEA) models of the Boltzmann equation. The models preserve the usual collision invariants (mass, momentum, energy), as well as the non-negativity of the phase-space distribution, and have a strong built-in thermodynamic consistency, i.e., they entail a general H-theorem valid even very far from equilibrium. This family of models features a molecular-speed-dependent collision frequency; each variant can be shown to approach a corresponding BGK model with the same variable collision frequency in the limit of small deviation from equilibrium. This includes power-law dependence on the molecular speed for which the BGK model is known to have a Prandtl number that can be adjusted via the power-law exponent. We compare numerical solutions of the constant and velocity-dependent collision frequency variants of the SEA model with the standard relaxation-time model and a Monte Carlo simulation of the original Boltzmann collision operator for hard spheres for homogeneous relaxation from near-equilibrium and highly non-equilibrium states. Good agreement is found between all models in the near-equilibrium regime. However, for initial states that are far from equilibrium, large differences are found; this suggests that the maximum entropy production statistical ansatz is not equivalent to Boltzmann collisional dynamics and needs to be modified or augmented via additional constraints or structure.
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Reports on the topic "Varianty montáže"

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Booth, T. E. Monte Carlo variance reduction approaches for non-Boltzmann tallies. Office of Scientific and Technical Information (OSTI), December 1992. http://dx.doi.org/10.2172/10115861.

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Cramer, S. N., and J. S. Tang. Variance reduction methods applied to deep-penetration Monte Carlo problems. Office of Scientific and Technical Information (OSTI), January 1986. http://dx.doi.org/10.2172/5970446.

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Turner, S. A. Automatic variance reduction for Monte Carlo simulations via the local importance function transform. Office of Scientific and Technical Information (OSTI), February 1996. http://dx.doi.org/10.2172/212579.

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Pearson, Eric, and Joel Kulesza. Proof that Combining the Forced-collision and DXTRAN Monte Carlo Variance-reduction Techniques is Fair. Office of Scientific and Technical Information (OSTI), August 2021. http://dx.doi.org/10.2172/1813833.

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Lo, Andrew, and A. Craig MacKinlay. The Size and Power of the Variance Ratio Test in Finite Samples: A Monte Carlo Investigation. Cambridge, MA: National Bureau of Economic Research, June 1988. http://dx.doi.org/10.3386/t0066.

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Ayoul-Guilmard, Q., S. Ganesh, M. Nuñez, R. Tosi, F. Nobile, R. Rossi, and C. Soriano. D5.4 Report on MLMC for time dependent problems. Scipedia, 2021. http://dx.doi.org/10.23967/exaqute.2021.2.005.

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In this report, we study the use of Multi-Level Monte Carlo (MLMC) methods for time dependent problems. It was found that the usability of MLMC methods depends strongly on whether or not the underlying time dependent problem is chaotic in nature. Numerical experiments are conducted on both simple problems, as well as fluid flow problems of practical interest to the ExaQUte project, to demonstrate this. For the non-chaotic cases, the hypotheses that enable the use of MLMC methods were found to be satisfied. For the chaotic cases, especially the case of high Reynolds’ number fluid flow, the hypotheses were not satisfied. However, it was found that correlations between the different levels were high enough to merit the use of multi-fidelity or control-variate approaches. It was also noted that MLMC methods could work for chaotic problems if the time window of analysis were chosen to be small enough. Future studies are proposed to examine this possibility.
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PORMC: A model for Monte Carlo simulation of fluid flow, heat, and mass transport in variably saturated geologic media. Office of Scientific and Technical Information (OSTI), September 1991. http://dx.doi.org/10.2172/5178632.

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