A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Abstract The Monte Carlo method may briefly be described as the numerical tool of studying an artificial stochastic model of a physical or mathematical process. This paper examines the basic principles of the method, which include the random numbers generation from an uniform density function, its extension for sampling from more complicated probability density functions, and the theory of estimation in straight-analogue (“crude”) simulation. The variance reduction techniques are also introduced for improving the efficiency of the Monte Carlo method. A brief comment is given about its use in uncertainty analysis. A clear example of the use of Monte Carlo in the system availability estimation is given.
Abstract The Monte Carlo method may briefly be described as the numerical tool of studying an artificial stochastic model of a physical or mathematical process. This paper examines the basic principles of the method, which include the random numbers generation from an uniform density function, its extension for sampling from more complicated probability density functions, and the theory of estimation in straight-analogue (“crude”) simulation. The variance reduction techniques are also introduced for improving the efficiency of the Monte Carlo method. A brief comment is given about its use in uncertainty analysis. A clear example of the use of Monte Carlo in the system availability estimation is given.
The Monte Carlo Method
Perlado, J. M. (author)
1990-01-01
21 pages
Article/Chapter (Book)
Electronic Resource
English
| NTIS | 1957
| Springer Verlag | 1999
| British Library Online Contents | 2000
Kinetic Monte Carlo Simulation
| Wiley | 2019