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Libri sul tema "Rare events simulation"

Autore: Grafiati

Pubblicato: 12 ottobre 2024

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1

Shi, Yixi. Rare Events in Stochastic Systems: Modeling, Simulation Design and Algorithm Analysis. [New York, N.Y.?]: [publisher not identified], 2013.

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2

Bucklew, James Antonio. Introduction to Rare Event Simulation. New York, NY: Springer New York, 2004. http://dx.doi.org/10.1007/978-1-4757-4078-3.

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3

Bucklew, James Antonio. Introduction to Rare Event Simulation. New York, NY: Springer New York, 2004.

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4

Rubino, Gerardo, e Bruno Tuffin, a cura di. Rare Event Simulation using Monte Carlo Methods. Chichester, UK: John Wiley & Sons, Ltd, 2009. http://dx.doi.org/10.1002/9780470745403.

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5

1955-, Rubino Gerardo, e Tuffin Bruno, a cura di. Rare event simulation using Monte Carlo methods. Hoboken, N.J: Wiley, 2009.

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6

Lamers, Eugen. Contributions to Simulation Speed-Up: Rare Event Simulation and Short-Term Dynamic Simulation for Mobile Network Planning. Wiesbaden: Vieweg+Teubner / GWV Fachverlage GmbH, Wiesbaden, 2008.

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7

Allen, Michael P., e Dominic J. Tildesley. Rare event simulation. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198803195.003.0010.

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Abstract (sommario):

The development of techniques to simulate infrequent events has been an area of rapid progress in recent years. In this chapter, we shall discuss some of the simulation techniques developed to study the dynamics of rare events. A basic summary of the statistical mechanics of barrier crossing is followed by a discussion of approaches based on the identification of reaction coordinates, and those which seek to avoid prior assumptions about the transition path. The demanding technique of transition path sampling is introduced and forward flux sampling and transition interface sampling are considered as rigorous but computationally efficient approaches.

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8

(Editor), Bruce J. Berne, Giovanni Cicotti (Editor) e David F. Coker (Editor), a cura di. Classical and Quantum Dynamics in Condensed Phase Simulations: Proceedings of the International School of Physics "Computer Simulation of Rare Events and ... Classical and Quantum Condensed-Phase syste. World Scientific Publishing Company, 1998.

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9

Bucklew, James A. Introduction to Rare Event Simulation. Springer, 2004.

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10

An introduction to rare event simulation. New York: Springer, 2003.

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11

Rubino, Gerardo, e Bruno Tuffin. Rare Event Simulation Using Monte Carlo Methods. Wiley & Sons, Incorporated, John, 2009.

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12

Rubino, Gerardo, e Bruno Tuffin. Rare Event Simulation Using Monte Carlo Methods. Wiley & Sons, Incorporated, John, 2009.

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13

Rubino, Gerardo, e Bruno Tuffin. Rare Event Simulation Using Monte Carlo Methods. Wiley & Sons, Limited, John, 2009.

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14

Clark, James S., Dave Bell, Michael Dietze, Michelle Hersh, Ines Ibanez, Shannon LaDeau, Sean McMahon et al. Assessing the probability of rare climate events. A cura di Anthony O'Hagan e Mike West. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780198703174.013.16.

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Abstract (sommario):

This article focuses on the use of Bayesian methods in assessing the probability of rare climate events, and more specifically the potential collapse of the meridional overturning circulation (MOC) in the Atlantic Ocean. It first provides an overview of climate models and their use to perform climate simulations, drawing attention to uncertainty in climate simulators and the role of data in climate prediction, before describing an experiment that simulates the evolution of the MOC through the twenty-first century. MOC collapse is predicted by the GENIE-1 (Grid Enabled Integrated Earth system model) for some values of the model inputs, and Bayesian emulation is used for collapse probability analysis. Data comprising a sparse time series of five measurements of the MOC from 1957 to 2004 are analysed. The results demonstrate the utility of Bayesian analysis in dealing with uncertainty in complex models, and in particular in quantifying the risk of extreme outcomes.

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15

Optimization under Uncertainty with Applications in Data-driven Stochastic Simulation and Rare-event Estimation. [New York, N.Y.?]: [publisher not identified], 2022.

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