A Monte Carlo Learning/Biasing Experiment with Intelligent Random Numbers
- 1 March 1986
- journal article
- research article
- Published by Taylor & Francis in Nuclear Science and Engineering
- Vol. 92 (3) , 465-481
- https://doi.org/10.13182/nse86-a17534
Abstract
A Monte Carlo learning and biasing technique that does its learning and biasing in the random number space rather than the physical phase space is described. The technique is probably applicable to all linear Monte Carlo problems, but no proof is provided here. Instead, the technique is illustrated with a simple Monte Carlo transport problem. Problems encountered, problems solved, and speculations about future progress are discussed.Keywords
This publication has 2 references indexed in Scilit:
- Importance Estimation in Forward Monte Carlo CalculationsNuclear Technology - Fusion, 1984
- Geometrical Splitting in Monte CarloNuclear Science and Engineering, 1982