![]() ![]() Hence, a total of fifteen sampling strategy combinations are explored herein. Moreover, these techniques are combined with three schemes for generating the underlying samples: Simple Sampling, Latin Hypercube Sampling and Antithetic Variates Sampling. This article presents a benchmark study, comparing Simple or Crude Monte Carlo with four modern sampling techniques: Importance Sampling Monte Carlo, Asymptotic Sampling, Enhanced Sampling and Subset Simulation which are studied over six problems. A literature survey shows that benchmark studies, comparing the performance of several techniques over several problems, are rarely found. However, when such new techniques are introduced, they are compared to one or two existing techniques, and their performance is evaluated over two or three problems. In recent years, new, intelligent and efficient sampling techniques for Monte Carlo simulation have been developed. ![]()
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