mcnp and the monte carlo method
Simulation and the Monte Carlo Method Second Edition potx
... techniques in Monte Carlo simulation, such as antithetic and common random numbers, control random variables, conditional Monte Carlo, stratified sampling, and importance sampling The last is the most ... enabling the flow of information and understanding necessary to meet their needs and fulfill their aspirations Today, bold new technologies are changing the way we live and learn Wiley will be there, ... analysis and optimization of both static and dynamic models We introduce the celebrated score function method for sensitivity analysis, and two alternative methods for Monte Carlo optimization, the...
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SIMULATION AND THE MONTE CARLO METHOD Episode 2 pdf
... 1.15.1 Lagrangian Method The main components of the Lagrangian method are the Lagrange multipliers and the Lagrange function, The method was developed by Lagrange in 1797 for the optimization ... the limiting distribution j T = (1 - r )(1,r, r ,r , ) for this Markov chain, and all the states are therefore j positive recurrent On the other hand, when p q, C n is either or infinite, and ... (X,Y ) and fx and fy are the (marginal) pdfs of X and Y, respectively In other words, the mutual information can be viewed as the CE that measures 32 PRELIMINARIES the distance between the joint...
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SIMULATION AND THE MONTE CARLO METHOD Episode 3 potx
... generate X from the cdf Gi 2.3.4 Acceptance-Rejection Method The inverse-transform and composition methods are direct methods in the sense that they deal directly with the cdf of the random variable ... from the pdf (2.20) and then assign to X a random sign The validity of this procedure follows from the symmetry of the standard normal distribution about zero 60 RANDOM NUMBER RANDOM VARIABLE, AND ... one-dimensional random variables from a prescribed distribution We consider the inverse-transform method, the alias method, the composition method, and the acceptance-rejection method 2.3.1 Inverse-Transform...
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SIMULATION AND THE MONTE CARLO METHOD Episode 4 potx
... approximation to the real system and incorporate most of the important aspects of the real system On the other hand, the model must not be so complex as to preclude its understanding and manipulation There ... namely, the simulation clock and the event list Finally, in Section 3.3 we further explain the ideas behind discrete-event simulation via a number of worked examples Simulation and the Monte Carlo Method, ... Programming, and Analysis SpringerVerlag, New York, 2001 J M Hammersley and D C Handscomb Monte Carlo Methods John Wiley & Sons, New York, 1964 M H Kalos and P A Whitlock Monte Carlo Methods, Volume...
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SIMULATION AND THE MONTE CARLO METHOD Episode 5 ppsx
... Sample paths for the two inventory processes Let D , and A, be the size of the i-th demand and the length of the i-th interdemand time, respectively We assume that both { D,} and { A , } are iid ... of the standard deviation of H , that is, the square root of ’ (4.29) In the percentile method, the upper and lower bounds of the (1- a ) 100%confidence interval fore are given by the - a / and ... further reduce the variance 5.5 STRATIFIED SAMPLING Stratified sampling is closely related to both the composition method of Section 2.3.3 and the conditional Monte Carlo method discussed in the...
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SIMULATION AND THE MONTE CARLO METHOD Episode 6 doc
... multiplying and dividing the integrand by f(x;w) We now replace the expected value in (5.57)by its sample (stochastic) counterpart and then take the optimal solution of the associated Monte Carlo program ... on a and H ( X ) is ignored In the special case of equal weights ( p , = l / m and N, = N / m ) , the estimator (5.34) reduces to (5.38) and the method is known as the systematic sampling method ... represents the original values u, and the reference values vi obtained by using (5.65) The numbers 1-32 correspond to the generators and the numbers 33-70 correspond to the lines Note that the data...
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SIMULATION AND THE MONTE CARLO METHOD Episode 7 potx
... adaptively, as with the CE and TLR methods THE HIT -AND- RUN SAMPLER 173 6.3 THE HIT -AND- RUN SAMPLER The hit -and- run sampler, pioneered by Robert Smith [24], is among the first MCMC samplers in the category ... independent nearest neighbor random walks in 9thatstart at X t andend when they step out o f One random walk is called the forward walk and the other is called the backward walk The bidirectional walk ... sense, the C E and VM methods are similar, because the C E method minimizes the Kullback-Leibler distance between g* and g 5.16 Repeat Problem 5.2 using importance sampling, where the lengths of the...
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SIMULATION AND THE MONTE CARLO METHOD Episode 8 doc
... Hessians, etc.) of the response function ! u) ( with respect to parameter vector u, and it is based on the score function and the Fisher inforSimulation and the Monte Carlo Method, Second Edition ... iterations Plot the histograms of j ( p x) and f ( 2I x) and find the sample means of these posteriors Compare them with the classical estimates d) Show that the true posterior pdf of p given the data ... SENSITIVITY ANALYSIS AND MONTE CARL0 OPTIMIZATION and then solve the latter by standard mathematical programming techniques The resultant optimal solution provides an estimator of the corresponding...
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SIMULATION AND THE MONTE CARLO METHOD Episode 9 doc
... of the CE method to several such problems, such as the max-cut problem and the TSP, and provide supportive numerical results on the performance of the algorithm Simulation and the Monte Carlo Method ... in 1990 and independently in 1989 by Reiman and Weiss [ 121, who called it the likelihoodratio method Since then, both the IPA and S F methods have evolved over the past decade or so and have ... solve the optimization problem (PN)by standard methods of mathematical programming The resultant optimal function value and the optimal decision vector of the program (PN)provide estimators of the...
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SIMULATION AND THE MONTE CARLO METHOD Episode 10 pot
... several applications of the CE method to combinatorial optimization, namely the max-cut, the bipartition and the TSP We demonstrate numerically the efficiency of the C E method and its fast convergence ... ,n} and a set of edges E between the nodes, partition the nodes of the graph into two arbitrary subsets V1 and V such that the sum of 254 THE CROSS-ENTROPY METHOD the weights (costs) ctI of the ... i } and {oi }the means and standard deviations of the components, the updating formulas are (see Problem 8.17) (8.46) and (8.47) where Xki is the i-th component of Xk and X I , , X, is a random...
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SIMULATION AND THE MONTE CARLO METHOD Episode 11 pps
... them are the standard CE, exponential change of measure (ECM), and the celebrated MinxEnt method [ 171 Here we shall us a particular modification of the MinxEnt method called the PME method and ... with the values l,-l, and in the clause matrix A , which indicates if the literal corresponds to the variable, its negation, or that neither appears in the clause If, for example, z3 = and at3 ... 0,1,0,1) is the only other assignment that renders all the clauses true The problem of deciding whether there exists a valid assignment, and indeed providing such a vector, is called the SAT-assignment...
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SIMULATION AND THE MONTE CARLO METHOD Episode 12 pptx
... some known p,o and Co, one determines 111 and 51,then j k and C1, and so on Notice and that 2, Ct not depend on the observations y1, y2, and can therefore be determined of-line The Kalman filter ... Simulation and the Monte Carlo Method, Second Edition By R.Y Rubinstein and D P Kroese Copyright @ 2007 John Wiley & Sons, Inc 315 316 APPENDIX Generally, the bij can be found from the recursive ... C,) distributed The objective is to obtain the filtering pdf f(xt ~ : and thepredictive pdf f(zt1 y1:t-1) ~ ) must be Gaussian, since these random vectors and YITt Observe that the joint pdf of...
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Fundamentals of the monte carlo method for neutral and charged particle transport
... that all uses of the Monte Carlo are for the purposes of understanding physical phenomena There are others uses of the Monte Carlo method for purely mathematical reasons, such as the determination ... Neumann and Ulam during the initial development of thermonuclear weapons6 Ulam and von Neumann coined the phrase Monte Carlo and were pioneers in the development of the Monte Carlo technique and ... MONTE CARLO Basic understanding Figure 1.2: The role of Monte Carlo methods in basic science possible, as in the example of Figure 1.1 where two people can not occupy the same seat, a Monte Carlo...
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SIMULATION AND THE MONTE CARL0 METHODS econd Edition pptx
... techniques in Monte Carlo simulation, such as antithetic and common random numbers, control random variables, conditional Monte Carlo, stratified sampling, and importance sampling The last is the most ... enabling the flow of information and understanding necessary to meet their needs and fulfill their aspirations Today, bold new technologies are changing the way we live and learn Wiley will be there, ... analysis and optimization of both static and dynamic models We introduce the celebrated score function method for sensitivity analysis, and two alternative methods for Monte Carlo optimization, the...
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Monte Carlo Methods and Models in Finance and Insurance doc
... 3.2.2 The crude Monte Carlo method 57 3.2.3 The Monte Carlo method: Some first applications 60 3.3 Improving the speed of convergence of the Monte Carlo method: Variance reduction methods ... 51 52 53 53 53 The Monte Carlo Method: Basic Principles 55 3.1 Introduction 55 3.2 The strong law of large numbers and the Monte Carlo method 56 3.2.1 The strong law ... Monte Carlo Methods and Models in Finance and Insurance CHAPMAN & HALL/CRC Financial Mathematics Series Aims and scope: The field of financial mathematics forms an ever-expanding slice of the...
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Báo cáo hóa học: " Research Article Non-Pilot-Aided Sequential Monte Carlo Method to Joint Signal, Phase Noise, and Frequency " ppt
... between the CDF of both the real and imaginary part of the OFDM signal and the CDF of a Gaussian random variable with zero mean and variance 1/2 The summand in (B.3) is the product of the likelihood ... approximation for the multicarrier signal increases with both the number of subcarriers and the size of the constellation Moreover, the approximation accuracy for the real and imaginary part of the multicarrier ... accuracy as a function of the SNR The performance of the proposed estimator is compared to the PCRB For βT = 10−3 , it performs close to the PCRB The gap between the PCRB and the JSCPE-MPF increases...
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Báo cáo hóa học: " Research Article Sequential Monte Carlo Methods for Joint Detection and Tracking of Multiaspect Targets in Infrared Radar Images" pptx
... target aspect and motion and review the observation and clutter models focusing on the GMRf representation of the background and the derivation of the associated likelihood function for the observed ... ]T , that collects the positions, xn and yn , and ˙ ˙ the velocities, xn and yn , of the target’s centroid in a system of 2D Cartesian coordinates (x, y) On the other hand, the target’s aspect ... I, and the initial probabilities Pr({z0 = i}), i ∈ I where ζ and ζ are the spatial resolutions of the image, respectively, in the directions x and y The parameter pa in (2) denotes in turn the...
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APPLICATIONS OF MONTE CARLO METHOD IN SCIENCE AND ENGINEERING_2 pot
... the spins toward the [100] and the [010] directions grow and form one big DW at around B=0.85 Then the DW was fixed and the spins in the two domains gradually rotate toward the [110] direction, ... E2A, E2B Then E2 = E2 A + E2 B ; • (7) the difference of the energies before and after the exchange of the points A and B is ΔE = E2 − E1 ; • (6) (8) if ∆E ≤ 0, the exchange of the sites A and B ... and (b) The susceptibility of (a) diverges around temperature kBT=1.0 and the magnetic property shows ferro-magnetism The direction of the 546 Applications of Monte Carlo Method in Science and Engineering...
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APPLICATIONS OF MONTE CARLO METHOD IN SCIENCAPPLICATIONS OF MONTE CARLO METHOD IN SCIENCE AND ENGINEERING_1E AND ENGINEERING_1 doc
... Stubos and Theodore A Steriotis Chapter 27 Effect of the Repulsive Interactions on the Nucleation and Island Growth: Kinetic Monte Carlo Simulations 677 Hu Juanmei and Wu Fengmin Chapter 28 Monte Carlo ... detector The task itself demands a certain image quality which depends also on the X-ray spectrum, the examination geometry and furthermore on the size of the X-ray source’s focal spot and the resolution ... between the cathode (the electron emitter) and the anode (the X-ray target) When the electrons hit the target, they are decelerated hard by collisions with electrons of the target material or in the...
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