Monte Carlo Simulation
INTRODUCTION:
Monte Carlo simulations is a computerized mathematical technique used to model the probability of different outcomes and to understand the impact of risk and uncertainty in prediction and forecasting models. It is powerful statistical analysis tool has widely range of application in both non-engineering fields and engineering fields. Initially it was used at Alamos Scientific Laboratory to solve neutron diffusion problems in atomic bomb work.
Monte Carlo
simulation was coined after the city of Monte Carlo in Monaco, which is well known
for gambling such as roulette, dice, and slot machines. This computational
method was invented by Polish mathematician and nuclear physicist, Stanislaw
Ulam, in 1946 while taking in account the probabilities of winning a card game
of solitaire. He also participated in the Manhattan Project during WWII.
Monte Carlo simulations is a computerized mathematical technique used to model the probability of different outcomes and to understand the impact of risk and uncertainty in prediction and forecasting models. It is powerful statistical analysis tool has widely range of application in both non-engineering fields and engineering fields. Initially it was used at Alamos Scientific Laboratory to solve neutron diffusion problems in atomic bomb work.
WORKING PRINCIPLE:
It is done by random sampling of large number of experiments through computer efforts and then the characteristics of outcomes are observed. Every performed experiment has set of input random variables X = ( x1,x2,...) which are sampled according to their distribution. Then the values of the output variable Y are calculated through the performance function Y =g( X ) at the samples of input random variables. A number of experiments are carried out in this manner and a set of output variable Y is obtained for the statistical analysis
REFERENCES:
- http://www.palisade.com/risk/monte_carlo_simulation.asp
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