-
From the Flow section of the action bar,
click Monte Carlo
 and drop it on
the process diagram.
- Double-click Monte Carlo.
-
From the Monte Carlo Editor that appears,
select the General tab, and select the
Sampling technique.
| Option | Description |
|---|
| Simple Random Sampling | The default
selection, the easiest to understand, and the most commonly used sampling method. Sample points
for simulation are generated randomly and independently. |
|---|
| Descriptive Sampling | The recommended
method if the Monte Carlo simulation with the Simple Random Sampling technique becomes computationally expensive. Fewer simulations are required to estimate the statistical characteristics
of the system behavior. |
|---|
| Sobol Sampling | Generates numbers as binary fractions of appropriate length from a set of special binary fractions. |
|---|
- Enter the Number of Simulations.
Specifying a higher number of simulations
generally results in an increase in the accuracy level of the
statistical predictions. - Enter a value for the Random Seed.
Optimization
Process Composer seeds the random number generator used by the Monte Carlo algorithm using the value you
provide. As a result, all executions of the Monte Carlo adapter will use the same sequence
of random numbers and, therefore, will produce the same design points. This is useful for
debugging the Monte Carlo process when it is necessary to reproduce the same sequence of
design points. If you enter a value of -1 (default), Optimization
Process Composer seeds the random number generator using the clock time at the moment of execution.
-
Click Ok to save your changes
and to close the Monte Carlo Editor.
|