Relevant bibliographies by topics / Probabilities – Computer simulations

Contents

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

Academic literature on the topic 'Probabilities – Computer simulations'

Author: Grafiati
Published: 4 June 2021
Last updated: 8 February 2022

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Journal articles on the topic "Probabilities – Computer simulations"

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DOBRESCU, GIANINA, M. RUSU, and M. VASS. "COMPUTER SIMULATIONS OF FRACTAL SURFACES: APPLICATION IN ADSORPTION." Fractals 01, no. 03 (September 1993): 430–38. http://dx.doi.org/10.1142/s0218348x93000459.

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A computer program which is able to simulate adsorption on fractal surfaces was developed. The fractal surfaces are generated as Takagi surfaces. The computer program is based on a DLA-algorithm. Adsorption was simulated in different conditions: 1. equivalent active sites (homogeneous surfaces); 2. active sites with different adsorption probabilities; the probability associated with every active site is computed using a van der Waals potential. Our simulation allows us to explore the actual structure of the gas-solid interface and to study the sensitivity to energetic disorder. The fractal dim
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Smith, Peter J. "Underestimation of Rare Event Probabilities in Importance Sampling Simulations." SIMULATION 76, no. 3 (March 2001): 140–50. http://dx.doi.org/10.1177/003754970107600301.

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Peng, Xidan, and Xiangyang Li. "Performance Analysis for Analog Network Coding with Imperfect CSI in FDD Two Way Channels." Journal of Systems Science and Information 3, no. 4 (August 25, 2015): 357–64. http://dx.doi.org/10.1515/jssi-2015-0357.

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AbstractA time-division duplex (TDD) two-way channel exploits reciprocity to estimate the forward channel gain from the reverse link. Many previous works explore outage probabilities in the TDD system, based on the reciprocity property. However, a frequency-division duplex (FDD) system has no reciprocity property. In this letter, we investigate the impact of CSI estimation error on the performance of non-orthogonal and orthogonal analog network coding protocols in an FDD two-way system, where channel gains are independent of each other. Considering imperfect CSI, the closed-form expressions of
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SCHURZ, GERHARD, and PAUL D. THORN. "REWARD VERSUS RISK IN UNCERTAIN INFERENCE: THEOREMS AND SIMULATIONS." Review of Symbolic Logic 5, no. 4 (July 4, 2012): 574–612. http://dx.doi.org/10.1017/s1755020312000184.

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AbstractSystems oflogico-probabilistic(LP) reasoning characterize inference from conditional assertions that express high conditional probabilities. In this paper we investigate four prominent LP systems, the systemsO, P,Z, andQC. These systems differ in the number of inferences they licence (O⊂ P ⊂Z⊂QC). LP systems that license more inferences enjoy the possiblerewardof deriving more true and informative conclusions, but with this possible reward comes theriskof drawing more false or uninformative conclusions. In the first part of the paper, we present the four systems and extend each of them
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Shchur, Lev N., and Sergey S. Kosyakov. "Probability of Incipient Spanning Clusters in Critical Square Bond Percolation." International Journal of Modern Physics C 08, no. 03 (June 1997): 473–81. http://dx.doi.org/10.1142/s0129183197000394.

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The probability of simultaneous occurrence of at least k spanning clusters has been studied by Monte Carlo simulations on the 2D square lattice with free boundaries at the bond percolation threshold pc =1/2. It is found that the probability of k and more Incipient Spanning Clusters (ISC) have the values P(k>1) ≈ 0.00658(3) and P(k>2) ≈ 0.00000148(21) provided that the limit of these probabilities for infinite lattices exists. The probability P(k>3) of more than three ISC could be estimated to be of the order of 10-11 and is beyond the possibility to compute such a value by nowadays co
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Paschalidis, I. C., and S. Vassilaras. "Importance Sampling for the Estimation of Buffer Overflow Probabilities via Trace-Driven Simulations." IEEE/ACM Transactions on Networking 12, no. 5 (October 2004): 907–19. http://dx.doi.org/10.1109/tnet.2004.836139.

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Ojha, Durga Prasad. "Nematogenic Behaviour of a Cyano-Compound Using Quantum Mechanics and Computer Simulations." Zeitschrift für Naturforschung A 56, no. 3-4 (April 1, 2001): 319–25. http://dx.doi.org/10.1515/zna-2001-0315.

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Abstract Using quantum mechanics and intermolecular forces, the molecular ordering of a nematogenic cya-no-compound, 5-(frans-4-ethylcyclohexyl)-2-(4-cyanophenyl)-pyrimidine (ECCPP), has been exam­ ined. The CNDO/2 method has been employed to evaluate the net atomic charge and the dipole mo­ ment components at each atomic centre of the molecule. The configuration energy has been computed using the modified Rayleigh-Schrödinger perturbation method at intervals of 1Ä in translation and 10P in rotations, and corresponding probabilities have been calculated using Maxwell-Boltzmann statistics. The
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Chiou, Rong Nan, and Chia-Nian Shyi. "Adaptive Maximums of Random Variables for Network Simulations." Journal of Computer Systems, Networks, and Communications 2009 (2009): 1–6. http://dx.doi.org/10.1155/2009/383720.

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In order to enhance the precision of network simulations, the paper proposes an approach to adaptively decide the maximum of random variables that create the discrete probabilities to generate nodal traffic on simulated networks. In this paper, a statistical model is first suggested to manifest the bound of statistical errors. Then, according to the minimum probability that generates nodal traffic, a formula is proposed to decide the maximum. In the formula, a precision parameter is used to present the degree of simulative accuracy. Meanwhile, the maximum adaptively varies with the traffic dis
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Zhang, Xulong, and Xiaoxia Song. "Stability Analysis of a Dynamical Model for Malware Propagation with Generic Nonlinear Countermeasure and Infection Probabilities." Security and Communication Networks 2020 (September 22, 2020): 1–7. http://dx.doi.org/10.1155/2020/8859883.

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The dissemination of countermeasures is widely recognized as one of the most effective strategies of inhibiting malware propagation, and the study of general countermeasure and infection has an important and practical significance. On this point, a dynamical model incorporating generic nonlinear countermeasure and infection probabilities is proposed. Theoretical analysis shows that the model has a unique equilibrium which is globally asymptotically stable. Accordingly, a real network based on the model assumptions is constructed, and some numerical simulations are conducted on it. Simulations
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Lerche, Ian, and Brett S. Mudford. "How Many Monte Carlo Simulations Does One Need to Do?" Energy Exploration & Exploitation 23, no. 6 (December 2005): 405–27. http://dx.doi.org/10.1260/014459805776986876.

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This article derives an estimation procedure to evaluate how many Monte Carlo realizations need to be done in order to achieve prescribed accuracies in the estimated mean value and also in the cumulative probabilities of achieving values greater than, or less than, a particular value as the chosen particular value is allowed to vary. In addition, by inverting the argument and asking what the accuracies are that result for a prescribed number of Monte Carlo realizations, one can assess the computer time that would be involved should one choose to carry out the Monte Carlo realizations. These tw
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Dissertations / Theses on the topic "Probabilities – Computer simulations"

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Peng, Linghua. "Normalizing constant estimation for discrete distribution simulation /." Digital version accessible at:, 1998. http://wwwlib.umi.com/cr/utexas/main.

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Heimbigner, Stephen. "Implications in using Monte Carlo simulation in predicting cardiovascular risk factors among overweight children and adolescents a stochastic computer model based on probabilities from the Bogalusa Heart Study /." unrestricted, 2007. http://etd.gsu.edu/theses/available/etd-07252007-234503/.

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Thesis (M.P.H.)--Georgia State University, 2007.<br>Title from file title page. Russ Toal, committee chair; Michael Eriksen, Valerie Hepburn, committee members. Electronic text (102 p. : ill. (some col.)) : digital, PDF file. Description based on contents viewed Mar. 26, 2008. Includes bibliographical references (p. 71-73).
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Coelho, Renato Schattan Pereira 1987. "Simulação de multidões e planejamento probabilístico para otimização dos tempos de semáforos." [s.n.], 2012. http://repositorio.unicamp.br/jspui/handle/REPOSIP/275643.

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Orientadores: Siome Klein Goldenstein, Jacques Wainer<br>Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Computação<br>Made available in DSpace on 2018-08-22T23:53:33Z (GMT). No. of bitstreams: 1 Coelho_RenatoSchattanPereira_M.pdf: 864445 bytes, checksum: 8f57902047a23925af4b81fa0d7f3188 (MD5) Previous issue date: 2013<br>Resumo: O trânsito é um problema cada vez maior nas cidades, consumindo recursos e agravando a poluição; em São Paulo perdem-se cerca de R$33 bilhões por ano por causa do trânsito. Neste trabalho de mestrado desenvolvemos um sistema que une as áreas
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Deng, Yuxin. "Axiomatisations et types pour des processus probabilistes et mobiles." Phd thesis, École Nationale Supérieure des Mines de Paris, 2005. http://tel.archives-ouvertes.fr/tel-00155225.

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Cette th`ese se concentre sur des bases th´eoriques utiles pour l'analyse d'algorithmes et de protocoles<br />pour des syst`emes r´epartis modernes. Deux caract´eristiques importantes des mod`eles pour<br />ces syst`emes sont les probabilit´es et la mobilit´e typ´ee : des probabilit´es peuvent ˆetre utilis´ees pour<br />quantifier des comportements incertains ou impr´evisibles, et des types peuvent ˆetre utilis´es pour<br />garantir des comportements sˆurs dans des syst`emes mobiles. Dans cette th`ese nous d´eveloppons<br />des techniques alg´ebriques et des techniques bas´ees sur les types po
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Reuillon, Romain. "Simulations stochastiques en environnements distribués : application aux grilles de calcul." Phd thesis, Université Blaise Pascal - Clermont-Ferrand II, 2008. http://tel.archives-ouvertes.fr/tel-00731242.

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Contrairement aux modèles déterministes, le déroulement d'un modèle stochastique est conditionné par la réalisation de variables aléatoires. L'utilisation de hasard permet d'approcher un résultat le plus souvent incalculable de manière déterministe. En contrepartie, il est nécessaire d'estimer les paramètres des distributions associées aux quantités aléatoires en sortie du modèle stochastique. Ce calcul requiert l'exécution de multiples réplications indépendantes de la même expérience et de ce fait, d'une importante quantité de calcul. Toutes les simulations stochastiques comportent par concep
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Geffroy, Arthur. "Contribution a l'étude locale et globale de l'enveloppe convexe d'un échantillon aléatoire." Rouen, 1997. http://www.theses.fr/1997ROUES017.

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On définit le concept de plage d'appui d'un échantillon aléatoire, les plages d'appui étant certaines parties de l'enveloppe convexe pouvant coïncider avec l'enveloppe complète. On établit des formules générales pour l'espérance du nombre de sommets ou du nombre de cotes d'une plage d'appui quelconque, ainsi que l'espérance de sa longueur. Ces formules sont ensuite calculées dans le cas d'une loi normale dans le plan, d'une loi uniforme dans un polygone convexe, puis d'une loi uniforme dans une courbe convexe lisse. Des simulations informatiques permettent finalement d'étudier les vitesses de
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Baudrit, Cédric. "Représentation et propagation de connaissances imprécises et incertaines : application à l'évaluation des risques liés aux sites et aux sols pollués." Phd thesis, Université Paul Sabatier - Toulouse III, 2005. http://tel.archives-ouvertes.fr/tel-00011933.

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Actuellement, les choix relatifs à la gestion des sites potentiellement pollués s'appuient, notamment,<br />sur une évaluation des risques pour l'homme et l'environnement. Cette évaluation est effectuée à l'aide de modèles qui simulent le transfert de polluant depuis une source de pollution vers une cible vulnérable, pour différents scénarii d'exposition. La sélection des valeurs des paramètres de ces modèles s'appuie autant que possible sur les données recueillies lors des investigations de terrain (phase de diagnostic de site). Or pour des raisons de délais et de coûts, l'information recueil
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Touya, Thierry. "Méthodes d'optimisation pour l'espace et l'environnement." Phd thesis, Université Paul Sabatier - Toulouse III, 2008. http://tel.archives-ouvertes.fr/tel-00366141.

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Ce travail se compose de deux parties relevant d'applications industrielles différentes. <br />La première traite d'une antenne spatiale réseau active. <br />Il faut d'abord calculer les lois d'alimentation pour satisfaire les contraintes de rayonnement. Nous transformons un problème avec de nombreux minima locaux en un problème d'optimisation convexe, dont l'optimum est le minimum global du problème initial, en utilisant le principe de conservation de l'énergie. <br />Nous résolvons ensuite un problème d'optimisation topologique: il faut réduire le nombre d'éléments rayonnants (ER). Nous appl
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Patrix, Jérémy. "Détection de comportements à travers des modèles multi-agents collaboratifs, appliquée à l'évaluation de la situation, notamment en environnement asymétrique avec des données imprécises et incertaines." Phd thesis, Université de Caen, 2013. http://tel.archives-ouvertes.fr/tel-00991091.

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Ce manuscrit de thèse présente une méthode innovante brevetée pour la détection de comportements collectifs. En utilisant des procédés de fusion sur les données issues d'un réseau multi-capteurs, les récents systèmes de surveillance obtiennent les séquences d'observations des personnes surveillées. Ce bas niveau d'évaluation de la situation a été mesuré insuffisant pour aider les forces de sécurité lors des événements de foule. Afin d'avoir une plus haute évaluation de la situation dans ces environnements asymétriques, nous proposons une approche multi-agents qui réduit la complexité du problè
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Martin, Victorin. "Modélisation probabiliste et inférence par l'algorithme Belief Propagation." Phd thesis, Ecole Nationale Supérieure des Mines de Paris, 2013. http://tel.archives-ouvertes.fr/tel-00867693.

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On s'intéresse à la construction et l'estimation - à partir d'observations incomplètes - de modèles de variables aléatoires à valeurs réelles sur un graphe. Ces modèles doivent être adaptés à un problème de régression non standard où l'identité des variables observées (et donc celle des variables à prédire) varie d'une instance à l'autre. La nature du problème et des données disponibles nous conduit à modéliser le réseau sous la forme d'un champ markovien aléatoire, choix justifié par le principe de maximisation d'entropie de Jaynes. L'outil de prédiction choisi dans ces travaux est l'algorith
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Books on the topic "Probabilities – Computer simulations"

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Ross, Sheldon M. Simulation. 2nd ed. San Diego: Academic Press, 1997.

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Ross, Sheldon M. Simulation. 3rd ed. San Diego: Academic Press, 2002.

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Probability modeling and computer simulation: An integrated introduction with applications to engineering and computer science. Boston, Mass: PWS-Kent Pub. Co., 1988.

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Ross, Sheldon M. A course in simulation. New York: Macmillan, 1990.

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Baron, Michael. Probability and statistics for computer scientists. Boca Raton, FL: Chapman & Hall/CRC, 2007.

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Ross, Sheldon M. Simulation. 4th ed. Amsterdam: Elsevier Academic Press, 2006.

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Baron, Michael. Probability and statistics for computer scientists. Boca Raton, FL: Chapman & Hall/CRC, 2007.

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Probability, Markov chains, queues and simulation: The mathematical basis of performance modeling. Princeton: Princeton University Press, 2009.

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Intuitive probability and random processes using MATLAB. New York: Springer, 2005.

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1942-, Hillestad R. J., Rand Corporation, and European-American Center for Policy Analysis., eds. Modeling the external risks of airports for policy analysis. Santa Monica, CA: Rand, 1995.

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Book chapters on the topic "Probabilities – Computer simulations"

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Budde, Carlos E., and Arnd Hartmanns. "Replicating $$\textsc {Restart}$$ with Prolonged Retrials: An Experimental Report." In Tools and Algorithms for the Construction and Analysis of Systems, 373–80. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-72013-1_21.

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AbstractStatistical model checking uses Monte Carlo simulation to analyse stochastic formal models. It avoids state space explosion, but requires rare event simulation techniques to efficiently estimate very low probabilities. One such technique is $$\textsc {Restart}$$ R E S T A R T . Villén-Altamirano recently showed—by way of a theoretical study and ad-hoc implementation—that a generalisation of $$\textsc {Restart}$$ R E S T A R T to prolonged retrials offers improved performance. In this paper, we demonstrate our independent replication of the original experimental results. We implemented $$\textsc {Restart}$$ R E S T A R T with prolonged retrials in the and tools, and apply them to the models used originally. To do so, we had to resolve ambiguities in the original work, and refine our setup multiple times. We ultimately confirm the previous results, but our experience also highlights the need for precise documentation of experiments to enable replicability in computer science.
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Karvo, Jouni. "Efficient Simulation of Blocking Probabilities for Multi-layer Multicast Streams." In NETWORKING 2002: Networking Technologies, Services, and Protocols; Performance of Computer and Communication Networks; Mobile and Wireless Communications, 1020–31. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-47906-6_83.

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Bacharoudis, Konstantinos, Atanas Popov, and Svetan Ratchev. "Application of Advanced Simulation Methods for the Tolerance Analysis of Mechanical Assemblies." In IFIP Advances in Information and Communication Technology, 153–67. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-72632-4_11.

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AbstractIn the frame of a statistical tolerance analysis of complex assemblies, for example an aircraft wing, the capability to predict accurately and fast specified, very small quantiles of the distribution of the assembly key characteristic becomes crucial. The problem is significantly magnified, when the tolerance synthesis problem is considered in which several tolerance analyses are performed and thus, a reliability analysis problem is nested inside an optimisation one in a fully probabilistic approach. The need to reduce the computational time and accurately estimate the specified probabilities is critical. Therefore, herein, a systematic study on several state of the art simulation methods is performed whilst they are critically evaluated with respect to their efficiency to deal with tolerance analysis problems. It is demonstrated that tolerance analysis problems are characterised by high dimensionality, high non-linearity of the state functions, disconnected failure domains, implicit state functions and small probability estimations. Therefore, the successful implementation of reliability methods becomes a formidable task. Herein, advanced simulation methods are combined with in-house developed assembly models based on the Homogeneous Transformation Matrix method as well as off-the-self Computer Aided Tolerance tools. The main outcome of the work is that by using an appropriate reliability method, computational time can be reduced whilst the probability of defected products can be accurately predicted. Furthermore, the connection of advanced mathematical toolboxes with off-the-self 3D tolerance tools into a process integration framework introduces benefits to successfully deal with the tolerance allocation problem in the future using dedicated and powerful computational tools.
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Ababneh, Jafar, Hussein Abdel-Jaber, Firas Albalas, and Amjad Daoud. "Analyzing and Evaluating Current Computer Networks Simulation Models." In Simulation in Computer Network Design and Modeling, 459–78. IGI Global, 2012. http://dx.doi.org/10.4018/978-1-4666-0191-8.ch022.

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Computer simulation is widely-used in investigating the performance of existing and proposed systems in many areas of science, engineering, operations research, and management science, especially in applications characterized by complicated geometries and interaction probabilities, and for dealing with system design in the presence of uncertainty. This is particularly true in the case of computer systems and computer networks. Therefore, it is very important to have efficient, reliable, and accurate methodologies for simulating these systems to ensure effective, reliable, and accurate evaluation and analysis of performance and to create the optimum design parameters for communication and computer networks. Although practical experiments and simulations are the most widely used, several efforts have also been directed towards mathematical models. The main objectives of this chapter are to: present the methodologies and techniques used to evaluate and analyze the performance of communication and computer networks routers, such as mathematical analysis, computer simulations techniques, and empirical measurements; identify the workload required for accomplishing a simulation model or mathematical analysis; identify the main metrics used to evaluate, manage, and control the performance of the computer networks; present the advantage and disadvantage of these techniques; and identify the challenges facing these different methodologies.
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"Faking Probabilities: Computer Simulation." In Probabilities, 245–62. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2006. http://dx.doi.org/10.1002/9780470099797.ch9.

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"Faking Probabilities: Computer Simulation." In Probabilities, 285–304. Hoboken, NJ, USA: John Wiley & Sons, Inc, 2015. http://dx.doi.org/10.1002/9781118898864.ch9.

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Osais, Yahya E. "Simulating Probabilities." In Computer Simulation, 27–37. Chapman and Hall/CRC, 2017. http://dx.doi.org/10.1201/9781315120294-3.

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Khan, Mohammad S. "A Study of Computer Virus Propagation on Scale Free Networks Using Differential Equations." In Advanced Methods for Complex Network Analysis, 196–214. IGI Global, 2016. http://dx.doi.org/10.4018/978-1-4666-9964-9.ch008.

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The SIR model is used extensively in the field of epidemiology, in particular, for the analysis of communal diseases. One problem with SIR and other existing models is that they are tailored to random or Erdos type networks since they do not consider the varying probabilities of infection or immunity per node. In this paper, we present the application and the simulation results of the pSEIRS model that takes into account the probabilities, and is thus suitable for more realistic scale free networks. In the pSEIRS model, the death rate and the excess death rate are constant for infective nodes. Latent and immune periods are assumed to be constant and the infection rate is assumed to be a function of the size of the total population and the size of the infected population. A node recovers from an infection temporarily with a probability p and dies from the infection with probability (1-p).
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Biswas, Rathindra Nath, Swarup Kumar Mitra, and Mrinal Kanti Naskar. "Preserving Security of Mobile Anchors Against Physical Layer Attacks." In Cryptographic Security Solutions for the Internet of Things, 211–43. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-5742-5.ch008.

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This chapter introduces a new security scheme for mobile anchors avoiding the physical layer attacks towards localization in wireless sensor networks (WSNs). In a network, anchors are made location-aware equipping them with GPS (global positioning system) receivers. Direction finding capabilities are also incorporated with smart antennas. The proposed algorithm is based on adaptive beamforming of smart array that always minimizes the probabilities of successful attacks, keeping the adversaries beyond its beam coverage. Particle swarm optimization (PSO) technique is used to compute array excitation coefficients, generating the desired pattern. Thus, anchors remain secured through pattern irregularities, deteriorating the information retrieval process even though chances of occurring adequate RSS (received signal strength)/AoA (angle of arrival) measurements may exist. Moreover, anchors are assumed to send pseudo references towards stationary nodes over private links, preserving data integrity for localization. Simulation results validate its effectiveness over the existing methods.
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Biswas, Rathindra Nath, Swarup Kumar Mitra, and Mrinal Kanti Naskar. "Preserving Security of Mobile Anchors Against Physical Layer Attacks." In Research Anthology on Securing Mobile Technologies and Applications, 93–118. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-8545-0.ch006.

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This chapter introduces a new security scheme for mobile anchors avoiding the physical layer attacks towards localization in wireless sensor networks (WSNs). In a network, anchors are made location-aware equipping them with GPS (global positioning system) receivers. Direction finding capabilities are also incorporated with smart antennas. The proposed algorithm is based on adaptive beamforming of smart array that always minimizes the probabilities of successful attacks, keeping the adversaries beyond its beam coverage. Particle swarm optimization (PSO) technique is used to compute array excitation coefficients, generating the desired pattern. Thus, anchors remain secured through pattern irregularities, deteriorating the information retrieval process even though chances of occurring adequate RSS (received signal strength)/AoA (angle of arrival) measurements may exist. Moreover, anchors are assumed to send pseudo references towards stationary nodes over private links, preserving data integrity for localization. Simulation results validate its effectiveness over the existing methods.
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Conference papers on the topic "Probabilities – Computer simulations"

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Di Blasi, Marti´n, and Carlos Muravchik. "Leak Detection in a Pipeline Using Modified Line Volume Balance and Sequential Probability Tests." In 2006 International Pipeline Conference. ASMEDC, 2006. http://dx.doi.org/10.1115/ipc2006-10210.

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The use of statistical tools to improve the decision aspect of leak detection is becoming a common practice in the area of computer pipeline monitoring. Among these tools, the sequential probability ratio test is one of the most named techniques used by commercial leak detection systems [1]. This decision mechanism is based on the comparison of the estimated probabilities of leak or no leak observed from the pipeline data. This paper proposes a leak detection system that uses a simplified statistical model for the pipeline operation, allowing a simple implementation in the pipeline control sys
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Huei, Y. C., P. H. Keng, and N. Krivulin. "Average Network Blocking Probabilities for TDM WDM Optical Networks with OTSIs and without WC." In 2007 15th International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS). IEEE, 2007. http://dx.doi.org/10.1109/mascots.2007.12.

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Yassine, Ali A., Daniel E. Whitney, and Tony Zambito. "Assessment of Rework Probabilities for Simulatng Product Development Processes Using the Design Structure Matrix (DSM)." In ASME 2001 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2001. http://dx.doi.org/10.1115/detc2001/dtm-21693.

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Abstract This paper uses the Design Structure Matrix (DSM) to model and simulate the performance of development processes. Though the simulation is a powerful tool for analyzing process performance, its ability is limited by the quality of input information used in the analysis. DSM simulation requires process data that is hard to assess or estimate directly from development participants. In this paper, we propose a methodology that allows a more practical estimation of an important simulation parameter: rework probabilities. Furthermore, we show how does this assessment method (combined with
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Parameswaran, Nataraj, and Lidvin Kjerengtroen. "Determination of Failure Probabilities and Sensitivity Factors Based on First Order Reliability Method." In ASME 1994 Design Technical Conferences collocated with the ASME 1994 International Computers in Engineering Conference and Exhibition and the ASME 1994 8th Annual Database Symposium. American Society of Mechanical Engineers, 1994. http://dx.doi.org/10.1115/detc1994-0092.

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Abstract Traditionally, most engineering problems are modeled in such a manner that all the variables involved in the design equations are deterministic. By nature, however, seldom does such a phenomenon exist. Most of the variables involved are randomly distributed with a certain mean and standard deviation and follow a certain type of statistical distribution. This investigation compares two such statistical based design processes to evaluate failure probabilities of a one dimensional heat transfer problem with various statistically distributed parameters in its performance function. The met
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Wang, Zhonglai, Zissimos P. Mourelatos, Jing Li, Amandeep Singh, and Igor Baseski. "Time-Dependent Reliability of Dynamic Systems Using Subset Simulation With Splitting Over a Series of Correlated Time Intervals." In ASME 2013 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/detc2013-12257.

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Time-dependent reliability is the probability that a system will perform its intended function successfully for a specified time. Unless many and often unrealistic assumptions are made, the accuracy and efficiency of time-dependent reliability estimation are major issues which may limit its practicality. Monte Carlo simulation (MCS) is accurate and easy to use but it is computationally prohibitive for high dimensional, long duration, time-dependent (dynamic) systems with a low failure probability. This work addresses systems with random parameters excited by stochastic processes. Their respons
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Banerjee, Ashis G., Arvind Balijepalli, Satyandra K. Gupta, and Thomas W. LeBrun. "Radial Basis Function Based Simplified Trapping Probability Models for Optical Tweezers." In ASME 2008 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2008. http://dx.doi.org/10.1115/detc2008-49124.

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In order to automatically manipulate microspheres using optical tweezers in real-time, it is essential to efficiently compute an estimate of the probability with which they will be trapped by a moving laser beam in a spatial region close to its focus. This paper presents a radial basis function approach to generate simplified models for estimating trapping probability from the offline simulation data. The difference form of Langevin’s equation is used to perform offline particle motion simulation for estimating probabilities at discrete points. Gaussian radial basis functions combined with kd-
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Beck, James L., S. K. Au, and K. V. Yuen. "Bayesian Updating of Nonlinear Model Predictions Using Markov Chain Monte Carlo Simulation." In ASME 2001 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2001. http://dx.doi.org/10.1115/detc2001/vib-21398.

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Abstract The usual practice in system identification is to use system data to identify one model from a set of possible models and then to use this model for predicting system behavior. In contrast, the present robust predictive approach rigorously combines the predictions of all the possible models, appropriately weighted by their updated probabilities based on the data. This Bayesian system identification approach is applied to update the robust reliability of a dynamical system based on its measured response time histories. A Markov chain simulation method based on the Metropolis-Hastings a
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Wang, Yan. "Solving Interval Master Equation in Simulation of Jump Processes Under Uncertainties." In ASME 2013 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/detc2013-12740.

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Two types of uncertainty are generally recognized in modeling and simulation, including variability caused by inherent randomness and incertitude due to the lack of perfect knowledge. Generalized interval probability is able to model both uncertainty components simultaneously, where epistemic uncertainty is quantified by the generalized interval in addition to the probabilistic measure. With the conditioning, independence, and Markovian property uniquely defined, the calculus structures in generalized interval probability resembles those in the classical probability theory. An imprecise Markov
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Thakur, Atul, Petr Svec, and Satyandra K. Gupta. "Generation of State Transition Models Using Simulations for Unmanned Sea Surface Vehicle Trajectory Planning." In ASME 2011 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2011. http://dx.doi.org/10.1115/detc2011-48624.

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Trajectory planning for unmanned sea surface vehicles (USSVs) in high sea-states is a challenging problem. Large and somewhat stochastic ocean forces can cause significant deviations in the motion of the USSV. Controllers are employed to reject disturbances and get back on the desired trajectory. However, the position uncertainty can be still high and needs to be accounted for during the trajectory planning to circumvent collisions with the obstacles. We model the motion of the USSV as Markov decision process and use a trajectory planning approach based on stochastic dynamic programming. A key
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Xu, Yanwen, and Pingfeng Wang. "Sequential Sampling Based Reliability Analysis for High Dimensional Rare Events With Confidence Intervals." In ASME 2020 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/detc2020-22146.

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Abstract Analysis of rare failure events accurately is often challenging with an affordable computational cost in many engineering applications, and this is especially true for problems with high dimensional system inputs. The extremely low probabilities of occurrences for those rare events often lead to large probability estimation errors and low computational efficiency. Thus, it is vital to develop advanced probability analysis methods that are capable of providing robust estimations of rare event probabilities with narrow confidence bounds. Generally, confidence intervals of an estimator c
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