... traditional MonteCarlo methods have made an impact Lastly, a few misprints have been corrected, and we thank our colleagues for pointing them out Introduction 1.1 WHAT IS A MONTECARLO SIMULATION? In ... immediately applicable to simple sampling MonteCarlo methods However, as we shall see later, the usual form of MonteCarlo sampling, namely importance sampling Monte Carlo, leads to ‘dynamic’ correlations ... sequence of random integers Usually floating point numbers between and are needed; these are obtained by carrying out a floating point divide by the largest integer Nmax which can fit into a word One...
... ProQuest Information and Learning Company All rights reserved This microform edition is protected against unauthorized copying under Title 17, United States Code ProQuest Information and Learning ... 0.6 0.8 1.0 0.0 0.0 0.2 0.2 0.4 0.6 0.6 dim 0.4 dim 0.8 0.8 1.0 1.0 Pseudo sequence in 2D Sobol’ sequence in 2D ¨ p i ¤ § ¨ ¥ % wm wS6po ¨ w n y p q rmi vg q j j m...
... the cylindrical cluster using H1=HJ+HD+HA_macro+HB including the macroscopic anisotropy and H2=HJ+HD+HA_micro+HB 548 Applications of MonteCarlo Method in Science and Engineering including the ... phase lattice points can be arranged either in the form of grain inclusions, whiskers, 566 Applications of MonteCarlo Method in Science and Engineering fibers The influence of the input parameters ... 23 MonteCarlo Simulations of Grain Growth in Metals Sven K Esche Stevens Institute of Technology USA Introduction The application of the MonteCarlo (MC) method to simulate the grain growth in...
... 2011 Printed in India A free online edition of this book is available at www.intechopen.com Additional hard copies can be obtained from orders@intechweb.org Applications of MonteCarlo Method in ... 11 MonteCarlo Simulation of SEM and SAM Images 231 Y.G Li, S.F Mao and Z.J Ding Chapter 12 MonteCarlo Simulation of Insulating Gas Avalanche Development 297 Dengming Xiao Chapter 13 MonteCarlo ... Characterizing Molecular Rotations using MonteCarlo Simulations 451 Bart Verberck Chapter 18 Finite-time Scaling and its Applications to Continuous Phase Transitions 469 Fan Zhong Chapter 19 Using Monte...
... the host opens one out of the two remaining doors 7 Bias MonteCarlo Methods in Environmental Engineering Finally, the winning probability after switching from door #1 to #2 is calculated as ... number during 10 minutes! MonteCarlo sampling, called importance sampling, follows the same idea Instead of spanning all the possible cases and measuring a quantity of interest, sampling can be ... genetically engineering small animals has increased interest in vivo imaging of small animals The contents of chapter 11 are a paper by S Branco et al on using MonteCarlo methods in the evaluation...
... other In other words, arbitrage involves locking in a riskless profit by simultaneously entering into transactions in two or more markets Hedging is a trading strategy that involves reducing the ... pricing is done by applying numerical methods or combining them with Black-Scholes model, we will introduce three basic numerical methods including binomial trees, finite difference and MonteCarlo ... will introduce these basic numerical methods for option pricing one by one 2.3.1 Binomial Trees Binomial trees derivatives pricing model was originally presented by Cox, Ross, and Rubinstein in...
... RISING FALLING FALLING RISING RISING FALLING FALLING X1 = Sky clear or cloudy in the morning X2 = Barometer rising or falling in the morning X3 = Dry or wet in the afternoon Figure 2.1: The joint ... counting of large sets In this review, I outline the role of probabilistic inference in articial intelligence, present the theory of Markov chains, and describe various Markov chain MonteCarlo ... (2:1991, 2:1992b), Buntine and Weigend (2:1991), and Buntine (2:1992) have done interesting work using methods other than MonteCarlo I have applied Markov chain MonteCarlo methods to some of...
... corresponding to total energy deposited in detector by each particle For modeling the efficiencies of the hyperpure HP Ge detector (GMX) based on MCNP4C2 we need to provide an input file containing ... dissipated in the various materials or escaped out of the physical space included in the model For the interaction in the detector volume, MCNP4C2 produces a tally of the number of events in each ... self-absorption in sample itself, but also to the photon absorption in all other materials between the sample and the detector’s active part Monte- Carlo modeling allows to take into consideration...
... acids in the plasmin molecule, the amidolytic activity of two truncated plasmin variants was examined (Fig 8) Miniplasmin (des-kringle 1-4 plasmin) contains the kringle and the catalytic domain ... surface of fibrin Even if intravascular events initiate blood clotting and fibrin dissolution simultaneously in a process called intrinsic or internal fibrinolysis [15], plasmin is generated directly ... as plasmin inhibitors A Tanka-Salamon et al Fig Amidolytic activity of des-kringle plasmin derivatives in the presence of fatty acids The activity of 20 nM miniplasmin (A) and microplasmin (B)...
... simulation and MonteCarlo 1.1 Evaluating a definite integral 1.2 MonteCarlo is integral estimation 1.3 An example 1.4 A simulation using Maple 1.5 Problems 13 Uniform random numbers 2.1 Linear congruential ... grounding in the principles of simulation Chapter deals with the other burgeoning area of simulation, namely Markov chain MonteCarlo and its use in Bayesian statistics Here, I have been influenced ... explored in Chapter g 1.2 MonteCarlo is integral estimation How is it that the MonteCarlo method evolved from its rather specialized use in integral evaluation to its current status as a modelling...
... as intervening rivers or mountains, could be KLEIN similarly approximated The sudden splitting of a single speech community into two groups can be modeled by assigning zero probabilities of interaction ... The linguistic drift has direction In other words, only those individual variations embody it or carry it which move in a certain direction, just as only certain wave movements in the bay outline ... numbers for a fraction in the range 0-1, implementing the event only if that number were in the range 0-0.2 In evaluating the predictions of a system incorporating such decision-making devices, it is...
... Tesauro and G Galperin 1996 On-line policy improvement using Monte- Carlo search In Advances in Neural Information Processing 9, pages 1068–1074 Adam Vogel and Daniel Jurafsky 2010 Learning to follow ... 1268–1277 S.R.K Branavan, David Silver, and Regina Barzilay 2011 Non-linear monte- carlo search in civilization ii In Proceedings of IJCAI John S Bridle 1990 Training stochastic model recognition algorithms ... actions In Proceedings of ACL, pages 82–90 S.R.K Branavan, Luke Zettlemoyer, and Regina Barzilay 2010 Reading between the lines: Learning to map high-level instructions to commands In Proceedings...
... online and offline knowledge in UCT In 24th International Conference on Machine Learning (ICML’07), pages 273–280, June Levente Kocsis and Csaba Szepesvári 2006 Bandit based monte- carloplanning ... machine translation using paraphrases In HLT-NAACL 2006: Main Proceedings, pages 17–24, Morristown, NJ, USA Association for Computational Linguistics Sylvain Gelly and David Silver 2007 Combining ... algorithm Monte- Carlo based Paraphrase Generation UCT (Kocsis and Szepesvári, 2006) (Upper Confidence bound applied to Tree) is a Monte- Carloplanning algorithm that have some interesting properties:...
... without intent to infringe Library of Congress Cataloging in Publication Data Korn, Ralf MonteCarlo methods and models in finance and insurance / Ralf Korn, Elke Korn, Gerald Kroisandt p cm (Financial ... the building blocks for modelling the uncertainty inherent in financial markets Developing efficient MonteCarlo methods for L´vy models e is a very active area that still is at its beginning We therefore ... MonteCarlo Methods and Models in Finance and Insurance Serial test or m-tuple test The frequency test can be generalized in examining pairs of successive RNs Again we have partitioned the single...
... shows the corresponding tracking results for the same frame In order to obtain a quantitative assessment of tracking performance, we ran 100 independent MonteCarlo simulations using, respectively, ... “Multitarget tracking using a new soft-gating approach and sequential MonteCarlo methods,” in Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP ’05), ... FUTURE WORK We discussed in this paper a methodology for joint detection and tracking of multiaspect targets in remote sensing image sequences using sequential MonteCarlo (SMC) filters The proposed...
... The MonteCarlo method applied in this study is a classical full MonteCarlo method The calculation time was long for each case In recent a few years, various techniques have helped in increasing ... modulating devices for MonteCarlo treatment planning Med Phys 2004, 31:1235-1242 Ma C-M, Li JS, Pawlicki T, et al.: A MonteCarlo dose calculation tool for radiotherapy treatment planning Phys Med Biol ... (Figure 3) In the MonteCarlo simulations, the statistical uncertainties in the high dose regions, such as the GTV, are below 1% Other error sources include electron source parameters, linear accelerator...
... Dose-volume constraints for the critical structures were summarized in Table Intensity modulation was achieved using the sliding window technique [26] which was implemented in the VCU in- house IMRT ... JO, Mohan R: MonteCarlo dose calculations for dynamic IMRT treatments Phys Med Biol 2001, 46:929-941 Yang J, Li JS, Qin L, Xiong W, Ma CM: Modelling of electron contamination in clinical photon ... treatment planning optimization system Phys Med Biol 2000, 45:2483-2495 Ma CM, Mok E, Kapur A, Pawlicki T, Findley D, Brain S, Forster K, Boyer AL: Clinical implementation of a MonteCarlo treatment planning...
... simulation and MonteCarlo 1.1 Evaluating a definite integral 1.2 MonteCarlo is integral estimation 1.3 An example 1.4 A simulation using Maple 1.5 Problems 13 Uniform random numbers 2.1 Linear congruential ... grounding in the principles of simulation Chapter deals with the other burgeoning area of simulation, namely Markov chain MonteCarlo and its use in Bayesian statistics Here, I have been influenced ... explored in Chapter g 1.2 MonteCarlo is integral estimation How is it that the MonteCarlo method evolved from its rather specialized use in integral evaluation to its current status as a modelling...