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# Algorithms to Represent Statistical Properties of Probability Loops in Computer Simulation Programs

IP.com Disclosure Number: IPCOM000076046D
Original Publication Date: 1972-Jan-01
Included in the Prior Art Database: 2005-Feb-24
Document File: 3 page(s) / 31K

IBM

## Related People

Dreisbach, JW: AUTHOR [+2]

## Abstract

Computer simulation programs have traditionally been composed of flow diagrams with probabilistic branches. The illustrated flow diagrams describe three commonly modeled sequences of events.

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Algorithms to Represent Statistical Properties of Probability Loops in Computer Simulation Programs

Computer simulation programs have traditionally been composed of flow diagrams with probabilistic branches. The illustrated flow diagrams describe three commonly modeled sequences of events.

The flow diagram of Fig. 1 is often used to model search routines which are only entered conditionally (with probability P) and which have a probability, q, of finding the searched for data each event or access. Similarly, flow 1 may represent any subroutine which is conditionally entered, probability P, and conditionally exited, probability q.

The flow diagram of Fig. 2 is the special case of flow 1 with an unconditional entry. It may model a read or a write with the probability of an error, P, which will require a reread of a rewrite. It also may simulate the integration curve fit, or any iterative routine in which the successful completion of the routine depends on a random variable, e.g., the input data.

The flow diagram of Fig. 3 may be used to simulate sequences of events similar to that of flow 2. The difference being that the first execution of the event is conditional, probability P, just as repeated executions arc conditional. This could simulate a data smoothing program, which is executed whenever an out of limits condition is detected and which is repeated until the data is brought back into range.

Normally, a "random number" would be generated at each test block in order to perform the pro...