Relevant bibliographies by topics / Rare events simulation

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

Academic literature on the topic 'Rare events simulation'

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Published: 12 October 2024

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Journal articles on the topic "Rare events simulation"

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Becker, M., and P. L. Douillet. "Hierarchical Simulation For Rare Events." International Journal of Modelling and Simulation 17, no. 2 (January 1997): 66–71. http://dx.doi.org/10.1080/02286203.1997.11760314.

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Lagnoux, Agnès. "RARE EVENT SIMULATION." Probability in the Engineering and Informational Sciences 20, no. 1 (December 12, 2005): 45–66. http://dx.doi.org/10.1017/s0269964806060025.

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This article deals with estimations of probabilities of rare events using fast simulation based on the splitting method. In this technique, the sample paths are split into multiple copies at various stages in the simulation. Our aim is to optimize the algorithm and to obtain a precise confidence interval of the estimator using branching processes. The numerical results presented suggest that the method is reasonably efficient.
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Kubatur, Shruthi S., and Mary L. Comer. "Simulation of Rare Events in Images." Electronic Imaging 2018, no. 15 (January 28, 2018): 227–1. http://dx.doi.org/10.2352/issn.2470-1173.2018.15.coimg-227.

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Asmussen, Søren, Reuven Y. Rubinstein, and Chia-Li Wang. "Regenerative rare events simulation via likelihood ratios." Journal of Applied Probability 31, no. 3 (September 1994): 797–815. http://dx.doi.org/10.2307/3215157.

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In this paper we obtain some new theoretical and numerial results on estimation of small steady-state probabilities in regenerative queueing models by using the likelihood ratio (score function) method, which is based on a change of the probability measure. For simple GI/G/1 queues, this amounts to simulating the regenerative cycles by a suitable change of the interarrival and service time distribution, typically corresponding to a reference traffic intensity ρ0 which is < 1 but larger than the given one ρ. For the M/M/1 queue, the resulting gain of efficiency is calculated explicitly and shown to be considerable. Simulation results are presented indicating that similar conclusions hold for gradient estimates and in more general queueing models like queueing networks.
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Asmussen, Søren, Reuven Y. Rubinstein, and Chia-Li Wang. "Regenerative rare events simulation via likelihood ratios." Journal of Applied Probability 31, no. 03 (September 1994): 797–815. http://dx.doi.org/10.1017/s0021900200045356.

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In this paper we obtain some new theoretical and numerial results on estimation of small steady-state probabilities in regenerative queueing models by using the likelihood ratio (score function) method, which is based on a change of the probability measure. For simple GI/G/1 queues, this amounts to simulating the regenerative cycles by a suitable change of the interarrival and service time distribution, typically corresponding to a reference traffic intensity ρ 0 which is &lt; 1 but larger than the given one ρ. For the M/M/1 queue, the resulting gain of efficiency is calculated explicitly and shown to be considerable. Simulation results are presented indicating that similar conclusions hold for gradient estimates and in more general queueing models like queueing networks.
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Asmussen, Søren, Klemens Binswanger, Bjarne Højgaard, Soren Asmussen, and Bjarne Hojgaard. "Rare Events Simulation for Heavy-Tailed Distributions." Bernoulli 6, no. 2 (April 2000): 303. http://dx.doi.org/10.2307/3318578.

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Kabanov, A. A., and S. A. Dubovik. "Simulation of Rare Events in Stochastic Systems." Journal of Physics: Conference Series 2096, no. 1 (November 1, 2021): 012151. http://dx.doi.org/10.1088/1742-6596/2096/1/012151.

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Abstract The paper presents algorithms for simulation rare events in stochastic systems based on the theory of large deviations. Here, this approach is used in conjunction with the tools of optimal control theory to estimate the probability that some observed states in a stochastic system will exceed a given threshold by some upcoming time instant. Algorithms for obtaining controlled extremal trajectory (A-profile) of the system, along which the transition to a rare event (threshold) occurs most likely under the influence of disturbances that minimize the action functional, are presented. It is also shown how this minimization can be efficiently performed using numerical-analytical methods of optimal control for linear and nonlinear systems. These results are illustrated by an example for a precipitation-measured monsoon intraseasonal oscillation (MISO) described by a low-order nonlinear stochastic model.
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Townsend, J. K., Z. Haraszti, J. A. Freebersyser, and M. Devetsikiotis. "Simulation of rare events in communications networks." IEEE Communications Magazine 36, no. 8 (1998): 36–41. http://dx.doi.org/10.1109/35.707815.

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Chambers, W. G. "Simulation of rare events in Gaussian processes." Electronics Letters 29, no. 15 (1993): 1384. http://dx.doi.org/10.1049/el:19930927.

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Bréhier, Charles-Edouard, Maxime Gazeau, Ludovic Goudenège, and Mathias Rousset. "Analysis and simulation of rare events for SPDEs." ESAIM: Proceedings and Surveys 48 (January 2015): 364–84. http://dx.doi.org/10.1051/proc/201448017.

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Dissertations / Theses on the topic "Rare events simulation"

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Liu, Hong. "Rare events, heavy tails, and simulation." Diss., Connect to online resource, 2006. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3239435.

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Booth, Jonathan James. "New applications of boxed molecular dynamics : efficient simulation of rare events." Thesis, University of Leeds, 2016. http://etheses.whiterose.ac.uk/13101/.

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This work presents Boxed Molecular Dynamics (BXD), an efficient simulation tool for studying long time scale processes which are inaccessible to conventional methods of simulation. Boxed Molecular Dynamics is explained and introduced in the context of modelling the dynamics of proteins and peptides. Two major applications of Boxed Molecular Dynamics are reported. 1) - The mechanical unfolding of proteins induced by Atomic Force Microscopy methods is investigated. For the first time, experimental data is reproduced and unfolding pathways are investigated without the use of high artificial pulling forces which makes the simulation less realistic. 2) - A cheap and accurate in silico screening tool is developed to aid with the discovery and production of medicinal cyclic peptides. Enzymatic peptide cyclization is investigated by BXD and the ability of amino acid sequences to cyclize is predicted with an accuracy of 76%.
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Liu, Gang. "Rare events simulation by shaking transformations : Non-intrusive resampler for dynamic programming." Thesis, Université Paris-Saclay (ComUE), 2016. http://www.theses.fr/2016SACLX043/document.

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Cette thèse contient deux parties: la simulation des événements rares et le rééchantillonnage non-intrusif stratifié pour la programmation dynamique. La première partie consiste à quantifier des statistiques liées aux événements très improbables mais dont les conséquences sont sévères. Nous proposons des transformations markoviennes sur l'espace des trajectoires et nous les combinons avec les systèmes de particules en interaction et l'ergodicité de chaîne de Markov, pour proposer des méthodes performantes et applicables en grande généralité. La deuxième partie consiste à résoudre numériquement le problème de programmation dynamique dans un contexte où nous avons à disposition seulement des données historiques en faible nombre et nous ne connaissons pas les valeurs des paramètres du modèle. Nous développons et analysons un nouveau schéma composé de stratification et rééchantillonnage
This thesis contains two parts: rare events simulation and non-intrusive stratified resampler for dynamic programming. The first part consists of quantifying statistics related to events which are unlikely to happen but which have serious consequences. We propose Markovian transformation on path spaces and combine them with the theories of interacting particle system and of Markov chain ergodicity to propose methods which apply very generally and have good performance. The second part consists of resolving dynamic programming problem numerically in a context where we only have historical observations of small size and we do not know the values of model parameters. We propose and analyze a new scheme with stratification and resampling techniques
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DHAMODARAN, RAMYA. "EFFICIENT ANALYSIS OF RARE EVENTS ASSOCIATED WITH INDIVIDUAL BUFFERS IN A TANDEM JACKSON NETWORK." University of Cincinnati / OhioLINK, 2004. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1099073321.

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Freitas, Rodrigo Moura 1989. "Molecular simulation = methods and applications = Simulações moleculares : métodos e aplicações." [s.n.], 2013. http://repositorio.unicamp.br/jspui/handle/REPOSIP/278440.

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Orientador: Maurice de Koning
Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Física Gleb Wataghin
Made available in DSpace on 2018-08-23T00:50:21Z (GMT). No. of bitstreams: 1 Freitas_RodrigoMoura_M.pdf: 11496259 bytes, checksum: 41c29f22d80da01064cf7a3b9681b05f (MD5) Previous issue date: 2013
Resumo: Devido aos avanços conceptuais e técnicos feitos em física computacional e ciência dos materiais computacional nos estamos aptos a resolver problemas que eram inacessíveis a alguns anos atrás. Nessa dissertação estudamos a evolução de alguma destas técnicas, apresentando a teoria e técnicas de simulação computacional para estudar transições de fase de primeira ordem com ênfase nas técnicas mais avançadas de calculo de energia livre (Reversible Scaling) e métodos de simulação de eventos raros (Forward Flux Sampling) usando a técnica de simulação atomística da Dinâmica Molecular. A evolução e melhora da e ciência destas técnicas e apresentada junto com aplicações a sistemas simples que permitem solução exata e também ao caso mais complexo da transição de fase Martenstica. Também apresentamos a aplicação de métodos numéricos no estudo do modelo de Pauling para o gelo. Nos desenvolvemos e implementamos um novo algoritmo para a criação e ciente de estruturas de gelo desordenadas. Este algoritmo de geração de cristais de gelo nos permitiu criar células de gelo Ih de tamanhos que não eram possíveis antes. Usando este algoritmo abordamos o problema de efeitos de tamanho finito não estudados anteriormente
Abstract: Due to the conceptual and technical advances being made in computational physics and computational materials science we have been able to tackle problems that were inaccessible a few years ago. In this dissertation we study the evolution of some of these techniques, presenting the theory and simulation methods to study _rst order phase transitions with emphasis on state-of-the-art free-energy calculation (Reversible Scaling) and rare event (Forward Flux Sampling) methods using the atomistic simulation technique of Molecular Dynamics. The evolution and efficiency improvement of these techniques is presented together with applications to simple systems that allow exact solution as well as the more the complex case of Martensitic phase transitions. We also present the application of numerical methods to study Pauling\'s model of ice. We have developed and implemented a new algorithm for efficient generation of disordered ice structures. This ice generator algorithm allows us to create ice Ih cells of sizes not reported before. Using this algorithm we address finite size effects not studied before
Mestrado
Física
Mestre em Física
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Hewett, Angela Dawn. "Expecting the unexpected : to what extent does simulation help healthcare professionals prepare for rare, critical events during childbearing?" Thesis, University of Leeds, 2016. http://etheses.whiterose.ac.uk/15431/.

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Pregnancy and childbirth presents both rare and critical events for which healthcare professionals are required to acquire and maintain competent clinical skills. In theory, a skill demonstrated using simulation will transfer into practice competently and confidently; the strength of simulation appears to lie in its validity with clinical context. Evidence shows that some professionals have difficulty responding appropriately to unexpected critical events and, therefore, there were two main aims: 1) to learn more about how healthcare practitioners develop skills in order to prepare for and respond to rare, critical and emergency events (RCEE) during childbearing, 2) to uncover healthcare practitioners’ experiences of simulated practice. An explanatory sequential mixed methods approach consisted of a quantitative systematic review combined with a framework analysis of curricula documentation. Subsequently, a conceptual framework of simulation was explored through qualitative inquiry with twenty five healthcare professionals who care for childbearing women. Attribution theory proved useful in analysing these experiences. Findings illustrated the multifaceted and complex nature of preparation for RCEE. Simulation is useful when clinical exposure is reduced, has the potential for practice in a safe environment and can result in increased confidence, initially. In addition, teamwork, the development of expertise with experience, debriefing and governance procedures were motivational factors in preparedness. Realism of scenarios affected engagement if they were not associated with ‘real life’; with obstetric focus, simulation fidelity was less important and, when related to play, this negatively influenced the value placed on simulation. The value of simulation is positioned in the ability to ‘practise’ within ‘safe’ parameters and there is contradiction between this assumption and observed reality. Paradoxically, confidence in responding to RCEE was linked to clinical exposure and not simulation and was felt to decay over time, although the timeframe for diminution was unclear. Overwhelmingly, simulation was perceived as anxiety provoking and this affected engagement and learning. Data highlights ambiguity between the theoretical principles of simulation and the practical application.
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Rai, Ajit. "Estimation de la disponibilité par simulation, pour des systèmes incluant des contraintes logistiques." Thesis, Rennes 1, 2018. http://www.theses.fr/2018REN1S105/document.

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L'analyse des FDM (Reliability, Availability and Maintainability en anglais) fait partie intégrante de l'estimation du coût du cycle de vie des systèmes ferroviaires. Ces systèmes sont hautement fiables et présentent une logistique complexe. Les simulations Monte Carlo dans leur forme standard sont inutiles dans l'estimation efficace des paramètres des FDM à cause de la problématique des événements rares. C'est ici que l'échantillonnage préférentiel joue son rôle. C'est une technique de réduction de la variance et d'accélération de simulations. Cependant, l'échantillonnage préférentiel inclut un changement de lois de probabilité (changement de mesure) du modèle mathématique. Le changement de mesure optimal est inconnu même si théoriquement il existe et fournit un estimateur avec une variance zéro. Dans cette thèse, l'objectif principal est d'estimer deux paramètres pour l'analyse des FDM: la fiabilité des réseaux statiques et l'indisponibilité asymptotique pour les systèmes dynamiques. Pour ce faire, la thèse propose des méthodes pour l'estimation et l'approximation du changement de mesure optimal et l'estimateur final. Les contributions se présentent en deux parties: la première partie étend la méthode de l'approximation du changement de mesure de l'estimateur à variance zéro pour l'échantillonnage préférentiel. La méthode estime la fiabilité des réseaux statiques et montre l'application à de réels systèmes ferroviaires. La seconde partie propose un algorithme en plusieurs étapes pour l'estimation de la distance de l'entropie croisée. Cela permet d'estimer l'indisponibilité asymptotique pour les systèmes markoviens hautement fiables avec des contraintes logistiques. Les résultats montrent une importante réduction de la variance et un gain par rapport aux simulations Monte Carlo
RAM (Reliability, Availability and Maintainability) analysis forms an integral part in estimation of Life Cycle Costs (LCC) of passenger rail systems. These systems are highly reliable and include complex logistics. Standard Monte-Carlo simulations are rendered useless in efficient estimation of RAM metrics due to the issue of rare events. Systems failures of these complex passenger rail systems can include rare events and thus need efficient simulation techniques. Importance Sampling (IS) are an advanced class of variance reduction techniques that can overcome the limitations of standard simulations. IS techniques can provide acceleration of simulations, meaning, less variance in estimation of RAM metrics in same computational budget as a standard simulation. However, IS includes changing the probability laws (change of measure) that drive the mathematical models of the systems during simulations and the optimal IS change of measure is usually unknown, even though theroretically there exist a perfect one (zero-variance IS change of measure). In this thesis, we focus on the use of IS techniques and its application to estimate two RAM metrics : reliability (for static networks) and steady state availability (for dynamic systems). The thesis focuses on finding and/or approximating the optimal IS change of measure to efficiently estimate RAM metrics in rare events context. The contribution of the thesis is broadly divided into two main axis : first, we propose an adaptation of the approximate zero-variance IS method to estimate reliability of static networks and show the application on real passenger rail systems ; second, we propose a multi-level Cross-Entropy optimization scheme that can be used during pre-simulation to obtain CE optimized IS rates of Markovian Stochastic Petri Nets (SPNs) transitions and use them in main simulations to estimate steady state unavailability of highly reliably Markovian systems with complex logistics involved. Results from the methods show huge variance reduction and gain compared to MC simulations
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Picciani, Massimiliano. "Rare events in many-body systems : reactive paths and reaction constants for structural transitions." Phd thesis, Université Pierre et Marie Curie - Paris VI, 2012. http://tel.archives-ouvertes.fr/tel-00706510.

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Cette thèse aborde l'étude de phénomènes physiques fondamentaux, avec des applications aux matériaux d'intérêt nucléaire. Nous avons développé des méthodes pour l'étude d'évènements rares concernant des transitions structurales thermiquement activées dans des systèmes à N-corps. La première méthode consiste en la simulation numérique du courant de probabilité associé aux chemins réactifs. Après avoir dérivé les équations d'évolution du courant de probabilité, on échantillonne ce courant grâce à un algorithme de type Monte Carlo Diffusif. Cette technique, dénommée Transition Current Sampling, a été appliquée pour étudier les transitions structurales d'un agrégat de 38 atomes liés par un potentiel Lennard-Jones (LJ-38). Un deuxième algorithme, dénommée Transition Path Sampling avec bias de Lyapunov local (LyTPS), a ensuite été développé. LyTPS permet de calculer des taux de réaction à température finie en suivant la théorie des états de transition. Un biais statistique dérivant du maximum des exposantes de Lyapunov locaux est introduit pour accélérer l'échantillonnage de trajectoires réactives. Afin d'extraire la valeur des constantes de réaction d'équilibre depuis celle obtenues par LyTPS, on utilise le Multistate Bennett Acceptance Ratio. Nous avons à nouveau validé cette méthode sur l'agrégat LJ-38. LyTPS est ensuite utilisé pour calculer les constantes de migration des lacunes et di-lacunes dans le Fer-α, ainsi que l'entropie de migration associée. Ces constantes de réaction servent de paramètre d'input dans des codes de modélisation cinétique (First Passage Kinetic Monte Carlo) pour reproduire numériquement des recuits de résistivité de Fer-α après irradiation.
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Silva, lopes Laura. "Méthodes numériques pour la simulation d'évènements rares en dynamique moléculaire." Thesis, Paris Est, 2019. http://www.theses.fr/2019PESC1045.

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Dans les systèmes dynamiques aléatoires, tels ceux rencontrés en dynamique moléculaire, les événements rares apparaissent naturellement, comme étant liés à des fluctuations de probabilité faible. En dynamique moléculaire, le repliement des protéines, la dissociation protéine-ligand, et la fermeture ou l’ouverture des canaux ioniques dans les membranes, sont des exemples d’événements rares. La simulation d’événements rares est un domaine de recherche important en biophysique depuis presque trois décennies.En dynamique moléculaire, on est particulièrement intéressé par la simulation de la transition entre les états métastables, qui sont des régions de l’espace des phases dans lesquelles le système reste piégé sur des longues périodes de temps. Ces transitions sont rares, leurs simulations sont donc assez coûteuses et parfois même impossibles. Pour contourner ces difficultés, des méthodes d’échantillonnage ont été développées pour simuler efficacement ces événement rares. Parmi celles-ci les méthodes de splitting consistent à diviser l’événement rare en sous-événements successifs plus probables. Par exemple, la trajectoire réactive est divisée en morceaux qui progressent graduellement de l’état initial vers l’état final.Le Adaptive Multilevel Splitting (AMS) est une méthode de splitting où les positions des interfaces intermédiaires sont obtenues de façon naturelle au cours de l’algorithme. Les surfaces sont définies de telle sorte que les probabilités de transition entre elles soient constantes et ceci minimise la variance de l’estimateur de la probabilité de l’événement rare. AMS est une méthode avec peu de paramètres numériques à choisir par l’utilisateur, tout en garantissant une grande robustesse par rapport au choix de ces paramètres.Cette thèse porte sur l’application de la méthode adaptive multilevel splitting en dynamique moléculaire. Deux types de systèmes ont été étudiés. La première famille est constituée de modèles simples, qui nous ont permis d’améliorer la méthode. La seconde famille est faite de systèmes plus réalistes qui représentent des vrai défis, où AMS est utilisé pour avancer nos connaissances sur les mécanismes moléculaires. Cette thèse contient donc à la fois des contributions de nature méthodologique et numérique.Dans un premier temps, une étude conduite sur le changement conformationnel d’une biomolécule simple a permis de valider l’algorithme. Nous avons ensuite proposé une nouvelle technique utilisant une combinaison d’AMS avec une méthode d’échantillonnage préférentiel de l’ensemble des conditions initiales pour estimer plus efficacement le temps de transition. Celle-ci a été validée sur un problème simple et nos résultats ouvrent des perspectives prometteuses pour des applications à des systèmes plus complexes. Une nouvelle approche pour extraire les mécanismes réactionnels liés aux transitions est aussi proposée dans cette thèse. Elle consiste à appliquer des méthodes de clustering sur les trajectoires réactives générées par AMS. Pendant ce travail de thèse, l’implémentation de la méthode AMS pour NAMD a été améliorée. En particulier, ce manuscrit présente un tutoriel lié à cette implémentation. Nous avons aussi mené des études sur deux systèmes moléculaires complexes avec la méthode AMS. Le premier analyse l’influence du modèle d’eau (TIP3P et TIP4P/2005) sur le processus de dissociation ligand– β -cyclodextrine. Pour le second, la méthode AMS a été utilisée pour échantillonner des trajectoires de dissociation d’un ligand du domaine N-terminal de la protéine Hsp90
In stochastic dynamical systems, such as those encountered in molecular dynamics, rare events naturally appear as events due to some low probability stochastic fluctuations. Examples of rare events in our everyday life includes earthquakes and major floods. In chemistry, protein folding, ligandunbinding from a protein cavity and opening or closing of channels in cell membranes are examples of rare events. Simulation of rare events has been an important field of research in biophysics over the past thirty years.The events of interest in molecular dynamics generally involve transitions between metastable states, which are regions of the phase space where the system tends to stay trapped. These transitions are rare, making the use of a naive, direct Monte Carlo method computationally impracticable. To dealwith this difficulty, sampling methods have been developed to efficiently simulate rare events. Among them are splitting methods, that consists in dividing the rare event of interest into successive nested more likely events.Adaptive Multilevel Splitting (AMS) is a splitting method in which the positions of the intermediate interfaces, used to split reactive trajectories, are adapted on the fly. The surfaces are defined suchthat the probability of transition between them is constant, which minimizes the variance of the rare event probability estimator. AMS is a robust method that requires a small quantity of user defined parameters, and is therefore easy to use.This thesis focuses on the application of the adaptive multilevel splitting method to molecular dynamics. Two kinds of systems are studied. The first one contains simple models that allowed us to improve the way AMS is used. The second one contains more realistic and challenging systems, where AMS isused to get better understanding of the molecular mechanisms. Hence, the contributions of this thesis include both methodological and numerical results.We first validate the AMS method by applying it to the paradigmatic alanine dipeptide conformational change. We then propose a new technique combining AMS and importance sampling to efficiently sample the initial conditions ensemble when using AMS to obtain the transition time. This is validatedon a simple one dimensional problem, and our results show its potential for applications in complex multidimensional systems. A new way to identify reaction mechanisms is also proposed in this thesis.It consists in performing clustering techniques over the reactive trajectories ensemble generated by the AMS method.The implementation of the AMS method for NAMD has been improved during this thesis work. In particular, this manuscript includes a tutorial on how to use AMS on NAMD. The use of the AMS method allowed us to study two complex molecular systems. The first consists in the analysis of the influence of the water model (TIP3P and TIP4P/2005) on the β -cyclodextrin and ligand unbinding process. In the second, we apply the AMS method to sample unbinding trajectories of a ligand from the N-terminal domain of the Hsp90 protein
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Saggadi, Samira. "Simulation d'évènements rares par Monte Carlo dans les réseaux hautement fiables." Thesis, Rennes 1, 2013. http://www.theses.fr/2013REN1S055.

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Le calcul de la fiabilité des réseaux est en général un problème NP-difficile. On peut par exemple s’intéresser à la fiabilité des systèmes de télécommunications où l'on veut évaluer la probabilité qu’un groupe sélectionné de nœuds peuvent communiquer. Dans ce cas, un ensemble de nœuds déconnectés peut avoir des conséquences critiques, que ce soit financières ou au niveau de la sécurité. Une estimation précise de la fiabilité est ainsi nécessaire. Dans le cadre de ce travail, on s'intéresse à l’étude et au calcul de la fiabilité des réseaux hautement fiables. Dans ce cas la défiabilité est très petite, ce qui rend l’approche standard de Monte Carlo inutile, car elle nécessite un grand nombre d’itérations. Pour une bonne estimation de la fiabilité des réseaux au moindre coût, nous avons développé de nouvelles techniques de simulation basées sur la réduction de variance par échantillonnage préférentiel
Network reliability determination, is an NP-hard problem. For instance, in telecommunications, it is desired to evaluate the probability that a selected group of nodes communicate or not. In this case, a set of disconnected nodes can lead to critical financials security consequences. A precise estimation of the reliability is, therefore, needed. In this work, we are interested in the study and the calculation of the reliability of highly reliable networks. In this case the unreliability is very small, which makes the standard Monte Carlo approach useless, because it requires a large number of iterations. For a good estimation of system reliability with minimum cost, we have developed new simulation techniques based on variance reduction using importance sampling
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Books on the topic "Rare events simulation"

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

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Rubino, Gerardo, and Bruno Tuffin, eds. 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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1955-, Rubino Gerardo, and Tuffin Bruno, eds. Rare event simulation using Monte Carlo methods. Hoboken, N.J: Wiley, 2009.

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

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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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(Editor), Bruce J. Berne, Giovanni Cicotti (Editor), and David F. Coker (Editor), eds. 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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Bucklew, James A. Introduction to Rare Event Simulation. Springer, 2004.

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

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Book chapters on the topic "Rare events simulation"

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Ciccotti, G. "Molecular Dynamics Simulations of Nonequilibrium Phenomena and Rare Dynamical Events." In Computer Simulation in Materials Science, 119–37. Dordrecht: Springer Netherlands, 1991. http://dx.doi.org/10.1007/978-94-011-3546-7_6.

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Rubino, Gerardo. "Network Reliability, Performability Metrics, Rare Events and Standard Monte Carlo." In Advances in Modeling and Simulation, 401–20. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-10193-9_20.

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Wainrib, Gilles. "Some Numerical Methods for Rare Events Simulation and Analysis." In Lecture Notes in Mathematics, 73–95. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-32157-3_4.

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Asmussen, Søren. "Large Deviations in Rare Events Simulation: Examples, Counterexamples and Alternatives." In Monte Carlo and Quasi-Monte Carlo Methods 2000, 1–9. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/978-3-642-56046-0_1.

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Pelikan, Martin, Jiri Ocenasek, Simon Trebst, Matthias Troyer, and Fabien Alet. "Computational Complexity and Simulation of Rare Events of Ising Spin Glasses." In Genetic and Evolutionary Computation – GECCO 2004, 36–47. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-24855-2_4.

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Carney, Meagan, Holger Kantz, and Matthew Nicol. "Analysis and Simulation of Extremes and Rare Events in Complex Systems." In Advances in Dynamics, Optimization and Computation, 151–82. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-51264-4_7.

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D’Argenio, Pedro R., Carlos E. Budde, Matias David Lee, Raúl E. Monti, Leonardo Rodríguez, and Nicolás Wolovick. "The Road from Stochastic Automata to the Simulation of Rare Events." In ModelEd, TestEd, TrustEd, 276–94. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-68270-9_14.

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van Moorsel, Aad P. A., Boudewijn R. Haverkort, and Ignas G. Niemegeers. "Fault Injection Simulation: A Variance Reduction Technique for Systems with Rare Events." In Dependable Computing for Critical Applications 2, 115–34. Vienna: Springer Vienna, 1992. http://dx.doi.org/10.1007/978-3-7091-9198-9_6.

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Zimmermann, Armin. "Extended Reward Measures in the Simulation of Embedded Systems With Rare Events." In Embedded Systems – Modeling, Technology, and Applications, 43–52. Dordrecht: Springer Netherlands, 2006. http://dx.doi.org/10.1007/1-4020-4933-1_5.

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Puch, Stefan, Martin Fränzle, and Sebastian Gerwinn. "Quantitative Risk Assessment of Safety-Critical Systems via Guided Simulation for Rare Events." In Leveraging Applications of Formal Methods, Verification and Validation. Verification, 305–21. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-03421-4_20.

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Conference papers on the topic "Rare events simulation"

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Foo, Jasmine, and Kevin Leder. "Rare events in cancer recurrence timing." In 2012 Winter Simulation Conference - (WSC 2012). IEEE, 2012. http://dx.doi.org/10.1109/wsc.2012.6465239.

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Kim, Youngjun, Yonatan Gur, and Mykel J. Kochenderfer. "Heuristics for planning with rare catastrophic events." In 2017 Winter Simulation Conference (WSC). IEEE, 2017. http://dx.doi.org/10.1109/wsc.2017.8248024.

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Gordon, Steven, and David Garbin. "Of dual-core networks during rare events." In 2011 Winter Simulation Conference - (WSC 2011). IEEE, 2011. http://dx.doi.org/10.1109/wsc.2011.6148017.

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Fresnedo, R. D. "Quick simulation of rare events in networks." In the 21st conference. New York, New York, USA: ACM Press, 1989. http://dx.doi.org/10.1145/76738.76805.

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Wang, Xingyu, and Chang-Han Rhee. "Rare-Event Simulation for Multiple Jump Events in Heavy-Tailed Lévy Processes with Infinite Activities." In 2020 Winter Simulation Conference (WSC). IEEE, 2020. http://dx.doi.org/10.1109/wsc48552.2020.9383865.

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Estecahandy, Maider, Laurent Bordes, Stephane Collas, and Christian Paroissin. "Acceleration methods for Monte Carlo simulation of rare events." In 2015 Annual Reliability and Maintainability Symposium (RAMS). IEEE, 2015. http://dx.doi.org/10.1109/rams.2015.7105098.

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Navarro, Jose M., G. Hugo A. Parada, and Juan C. Duenas. "System Failure Prediction through Rare-Events Elastic-Net Logistic Regression." In 2014 2nd International Conference on Artificial Intelligence, Modelling & Simulation (AIMS). IEEE, 2014. http://dx.doi.org/10.1109/aims.2014.19.

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Guo, Yabing, Wenbing Chang, and Shenghan Zhou. "The research and simulation about rare events based on MCMC." In 2015 27th Chinese Control and Decision Conference (CCDC). IEEE, 2015. http://dx.doi.org/10.1109/ccdc.2015.7162009.

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"Resampling techniques for rare events prediction using data-driven and hydrological models." In 25th International Congress on Modelling and Simulation. Modelling and Simulation Society of Australia and New Zealand, 2023. http://dx.doi.org/10.36334/modsim.2023.zeinolabedini.

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Pang, Yanbo, Kota Tsubouchi, Takahiro Yabe, and Yoshihide Sekimoto. "Intercity Simulation of Human Mobility at Rare Events via Reinforcement Learning." In SIGSPATIAL '20: 28th International Conference on Advances in Geographic Information Systems. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3397536.3422244.

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Reports on the topic "Rare events simulation"

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Washio, Takashi. Model Learning for Probabilistic Simulation on Rare Events and Scenarios. Fort Belvoir, VA: Defense Technical Information Center, March 2015. http://dx.doi.org/10.21236/ada616937.

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Kollman, Craig. Rare event simulation in radiation transport. Office of Scientific and Technical Information (OSTI), October 1993. http://dx.doi.org/10.2172/10172053.

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Sarupria, Sapna, Steven Hall, and Ryan DeFever. Sampling Rare Events In Aqueous Systems Using Molecular Simulations. Office of Scientific and Technical Information (OSTI), June 2024. http://dx.doi.org/10.2172/2376138.

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Shortle, John F. New Approaches for Rare-Event Simulation and Decision Making. Office of Scientific and Technical Information (OSTI), September 2013. http://dx.doi.org/10.2172/1128906.

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Martin, S., Larry Daggett, Morgan Johnston, Chris Hewlett, Kiara Pazan, Mario Sanchez, Dennis Webb, Mary Allison, and George Burkley. Houston Ship Channel Expansion Improvement Project – Navigation Channel Improvement Study : ship simulation results. Coastal and Hydraulics Laboratory (U.S.), November 2021. http://dx.doi.org/10.21079/11681/42342.

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In 2020, the US Army Engineer Research and Development Center (ERDC), Coastal and Hydraulics Laboratory, provided technical oversight during a navigation study to assist the Galveston District evaluation of different channel widening alternatives for larger ships transiting the Houston Ship Channel (HSC), Texas. The widening proposals encompassed several areas of the HSC including the Bay Section, the Bayport Ship Channel, Barbours Cut Channel, and the Bayou Section. The study was performed at the San Jacinto College Maritime Technology and Training Center (SJCMTTC) Ship/Tug Simulator (STS) Facility in La Porte, TX. The SJCMTTC STS is a real-time simulator; therefore, events on the simulator happen at the same time rate as real life. A variety of environmental forces act upon the ship during the simulation transit. These include currents, wind, waves, bathymetry, and ship-to-ship interaction. Online simulations of the project were conducted at SJCMTTC over a 3-week period – May through June 2020. Several mariners including Houston Pilots and G&H tugboat Captains participated in the testing and validation exercises. ERDC oversight was performed remotely because of the COVID-19 pandemic. Results in the form of engineering observations, track plots, and pilot interviews were reviewed to develop final conclusions and recommendations regarding the final design.
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Dean, Thomas, and aul Dupuis. Splitting for Rare Event Simulation: A Large Deviations Approach to Design and Analysis. Fort Belvoir, VA: Defense Technical Information Center, January 2007. http://dx.doi.org/10.21236/ada476257.

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Wallace, Adam. Towards The Development of Rare Event Simulation Methods For Improved Mechanistic Understanding of Mineral Surface Reactivity. Office of Scientific and Technical Information (OSTI), September 2024. http://dx.doi.org/10.2172/2447356.

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Kushner, Harold, and Paul Dupuis. Stochastic Control and Numerical Methods with Applications to Communications. Game Theoretic/Subsolution to Importance Sampling for Rare Event Simulation. Fort Belvoir, VA: Defense Technical Information Center, November 2008. http://dx.doi.org/10.21236/ada499989.

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Chazel, Simon, Sophie Bernard, and Hassan Benchekroun. Energy transition under mineral constraints and recycling: A low-carbon supply peak. CIRANO, May 2023. http://dx.doi.org/10.54932/ezhr6690.

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What are the implications of primary mineral constraints for the energy transition? Low-carbon energy production uses green capital, which requires primary minerals. We build on the seminal framework for the transition from a dirty to a clean energy in Golosov et al. (2014) to incorporate the role played by primary minerals and their potential recycling. We characterize the optimal paths of the energy transition under various mineral constraint scenarios. Mineral constraints limit the development of green energy in the long run: low-carbon energy production eventually reaches a plateau. We run our simulations using copper as the limiting mineral and we allow for its full recycling. Even in the limiting case of a 100% recycling rate, after five to six decades green energy production is 50% lower than in the scenario with unlimited primary copper, and after 30 decades, GDP is 3–8% lower. In extension scenarios, we confirm that a longer life duration of green capital delays copper extraction and the green energy peak, whereas reduced recycling caps moves the peak in green energy production forward.
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Kotlikoff, Laurence J., Guillermo Lagarda, and Gabriel Marin. A Personalized VAT with Capital Transfers: A Reform to Protect Low-Income Households in Mexico. Inter-American Development Bank, July 2023. http://dx.doi.org/10.18235/0005028.

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The Value-Added Tax (VAT) is the most prevalent consumption tax globally, yet it is frequently deemed highly regressive. To address this, we propose a Personalized VAT (PVAT) devised in conjunction with a distributional policy. We aim to achieve three objectives: increase revenue collection, achieve progressivity, and disrupt the intergenerational dependency of low-income households. We use Mexico as a case study, showing that eliminating all special VAT regimes and standardizing the rate at 16% could contribute an additional 2.2% of GDP to fiscal revenues. However, such a reform could have severe negative welfare impacts on the poor. To tackle this dilemma, we propose several PVAT scenarios. Our results indicate that a PVAT could be fiscally neutral or even increase revenues by up to 0.83% of GDP, while benefiting the lowest-income households. Lastly, we analyze the general equilibrium effects of a PVAT and various distributional policies, including lump-sum and capital transfers. For this purpose, we employ an overlapping generations model calibrated for Mexico. Our simulations reveal welfare enhancing and output growth results through a PVAT policy that includes capital transfers, thereby presenting a viable strategy for breaking intergenerational dependency.
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