论文信息 - The Monte Carlo method in science and engineering: Theory and application

The Monte Carlo method in science and engineering: Theory and application

In this lecture, a pedagogical introduction is given to the general methodology and practice of the Monte Carlo method. Both the static and the dynamic Monte Carlo method are discussed, and the significance of the Monte Carlo method to the modeling of various large scale problems in science and engineering is emphasized.

Karsten M. Decker | K. M. Decker

[1] P. Carnevali,et al. Image processing by stimulated annealing , 1985 .

[2] C. D. Gelatt,et al. Optimization by Simulated Annealing , 1983, Science.

[3] G. Marsaglia,et al. A New Class of Random Number Generators , 1991 .

[4] F. James. A Review of Pseudorandom Number Generators , 1990 .

[5] Reuven Y. Rubinstein,et al. Simulation and the Monte Carlo method , 1981, Wiley series in probability and mathematical statistics.

[6] Marius Iosifescu,et al. Finite Markov Processes and Their Applications , 1981 .

[7] Donald Ervin Knuth,et al. The Art of Computer Programming , 1968 .

[8] Emile H. L. Aarts,et al. Simulated Annealing: Theory and Applications , 1987, Mathematics and Its Applications.

[9] Forrest B. Brown,et al. Monte Carlo methods for radiation transport analysis on vector computers , 1984 .

[10] Paolo Carnevali,et al. Image Processing by Simulated Annealing , 1985, IBM J. Res. Dev..

[11] N. Metropolis,et al. Equation of State Calculations by Fast Computing Machines , 1953, Resonance.